Systems and methods for scalable n-core stats aggregation

ABSTRACT

The present invention is directed towards systems and methods for aggregating and providing statistics from cores of a multi-core system intermediary between one or more clients and servers. The system may maintain in shared memory a global device number for each core of the multi-core system. The system may provide a thread for each core of the multi-core system to gather data from the corresponding core. A first thread may generate aggregated statistics from a corresponding core by parsing the gathered data from the corresponding core. The first thread may transfer the generated statistics to a statistics log according to a schedule. The system may adaptively reschedule the transfer by monitoring the operation of each computing thread. Responsive to a request from a client, an agent of the client may obtain statistics from the statistics log.

RELATED APPLICATIONS

The present application claims priority to U.S. Provisional PatentApplication No. 61/428,124, entitled “SYSTEMS AND METHODS FOR SCALABLEN-CORE STATS AGGREGATION”, filed Dec. 29, 2010, which is incorporatedherein by reference in its entirety for all purposes.

FIELD OF THE DISCLOSURE

The present application generally relates to data communicationnetworks. In particular, the present application relates to systems andmethods for providing scalable unified data representation of theaggregate performance records and statistics of a multi-core networkappliance.

BACKGROUND OF THE DISCLOSURE

In certain conventional network systems, an appliance or intermediarydevice is disposed in a network between one or more clients requestingweb content or a network service, and one or more servers providing therequested web content or service. In some cases, the applianceestablishes connections with the clients and servers and manages theconnections and flow of information between the clients and servers. Theappliance may employ security rules to ensure a measure of securecommunications, monitor response time of servers, configure networkconnections to balance loads to servers, maintain user session data, andattend to other tasks which assure or improve the quality ofcommunications supported by the appliance. In various implementations,an appliance or intermediary device may track and/or provide data aboutits operations or performance.

BRIEF SUMMARY OF THE DISCLOSURE

The present invention is directed towards systems and methods foraggregating and providing statistics from cores of a multi-core systemintermediary between one or more clients and servers. The system maymaintain, in shared memory, a global device number for each core of themulti-core system. The system may provide a thread for each core of themulti-core system to gather data from the corresponding core. A firstthread may generate aggregated statistics from a corresponding core byparsing the gathered data from the corresponding core. The first threadmay transfer the generated statistics to a statistics log. In someaspects, the present application is directed towards systems and methodsfor providing unified performance data and unified trace data for amulti-core appliance disposed in a network. In a multi-core appliance, aplurality of packet engines in operation on the appliance can managenetwork traffic between one or more clients and one or more servers. Thesystems and methods herein describe how the plurality of performance andtrace data generated by the plurality of packet engines can beefficiently managed and consolidated to provide an aggregate set ofperformance data or trace data.

In one aspect, the present disclosure is directed to a method foraggregating performance statistics from multiple cores of a systemintermediary between one or more clients and servers. The multiple coresmay process multiple network traffic streams between one or more clientsand servers. The method may include maintaining, in shared memory of amulti-core system intermediary between one or more clients and servers,a global device number for each core of the multi-core system. Each coremay include one or more packet engines processing network trafficbetween the one or more clients and servers. An aggregator of themulti-core system may execute a computing thread for each core of themulti-core system. A first computing thread of the aggregator maycollect statistics of network traffic processed by one or more packetengines on a first core. The first computing thread may transfer thestatistics with a marker to a statistics log of the multi-core system.The marker may correspond to a global device number of the first core.

In some embodiments, the aggregator may assign, for each core of themulti-core system, a global device number to a virtual machine executingon the core. The aggregator may assign, for each core of the multi-coresystem, a global device number to each virtual machine of the core, eachvirtual machine comprising one or more packet engines processing networktraffic between the one or more clients and servers. The aggregator mayconsolidate at least a portion of statistics collected from two or morecores of the multi-core system into a buffer. The first computing threadmay write the collected statistics to the statistics log according to aschedule of the aggregator. The aggregator may adaptively reschedule thetransfer by monitoring the operation of the first core.

In some embodiments, the first computing thread may transfer thecollected statistics unchanged to the statistics log. The multi-coresystem may maintain the statistics log for two or more cores of themulti-core system. The aggregator may send a notification to a firstclient of the one or more clients responsive to the transfer. Themulti-core system may provide to the one or more clients access to thestatistics log.

In another aspect, the present disclosure is directed to a system foraggregating performance statistics from multiple cores of a deviceintermediary between one or more clients and servers. The multiple coresmay process multiple network traffic streams between one or more clientsand servers. The system may include shared memory between multiple coresof the intermediary device, for maintaining a global device number foreach core of the multi-core system. Each core may include one or morepacket engines processing network traffic between the one or moreclients and servers. An aggregator of the intermediary device mayexecute a computing thread for each core of the multi-core system. Theaggregator may execute a first computing thread collecting statistics ofnetwork traffic processed by one or more packet engines on a first core.The aggregator may transfer the statistics with a marker to a statisticslog of the multi-core system. The marker may correspond to a globaldevice number of the first core.

In some embodiments, the aggregator assigns a global device number to avirtual machine executing on each core. The aggregator may assign aglobal device number to each virtual machine of each core. Each virtualmachine may include one or more packet engines processing networktraffic between the one or more clients and servers. The aggregator mayfurther consolidate at least a portion of statistics collected from twoor more cores of the multi-core system into a buffer. The firstcomputing thread may write the collected statistics to the statisticslog according to a schedule of the aggregator.

In some embodiments, the aggregator adaptively reschedules the transferby monitoring the operation of the first core. The first computingthread may transfer the collected statistics unchanged to the statisticslog. The aggregator may maintain the statistics log for two or morecores of the device. The aggregator may send a notification to a firstclient of the one or more clients responsive to the transfer. Theaggregator may provide the one or more clients access to the statisticslog.

In various embodiments, a system for aggregating network performancedata or trace data comprises an appliance disposed in a network betweena plurality of clients and a plurality of servers providing web contentor network services for clients, a plurality of packet engines inoperation on a plurality of cores of the appliance, and an aggregator inoperation on the appliance. In certain embodiments, a system foraggregating performance data of an appliance, which is intermediary to aplurality of clients and one or more servers in a networked system,comprises a plurality of packet engines executing on a plurality ofcores configured for operation with the appliance. Each packet engine,executing on a respective core, can collect performance data identifyingstatistics of a service provided by a server in communication with thepacket engine as well as data identifying statistics of a virtualservice provided by the packet engine. One or more of the packet enginescan manage network traffic associated with the service. In variousembodiments, the system further comprises an aggregator which executeson a core of the multi-core, multi-packet-engine appliance. Theaggregator can store to a buffer packet engine performance data obtainedfrom each packet engine, and consolidate all packet engine performancedata to identify unified performance data. In various embodiments, theunified performance data identifies statistics for network servicesmanaged by the appliance, in some embodiments as though the appliancecomprised a single-core processing device. Further, the aggregator canreceive a request from an agent for performance data of the appliance,and transmit the unified performance data in response to the request.

In certain embodiments, the system described above is adapted toaggregate trace data and provide a unified record of trace data for themulti-core, multi-packet-engine appliance. In such embodiments, eachpacket engine can capture trace information for network traffic receivedand/or transmitted by the packet engine. The aggregator can store to abuffer the trace information obtained from each packet engine, andconsolidate all trace information from the plurality of packet enginesto provide unified trace data of network traffic managed by theappliance. The unified trace data can be representative of the applianceas though the appliance were a single-core, single-packet-engine system.The aggregator can further receive a request from an agent for networktrace data of the appliance, and transmit the unified trace data ofnetwork traffic in response to the request.

An embodiment of a method for aggregating performance data of amulti-core, multi-packet-engine appliance can comprise collecting, byeach packet engine executing on a respective core of the appliance,packet engine performance data identifying statistics of a serviceprovided by a server as managed by each packet engine, storing to abuffer, by the aggregator executing on a core of the appliance, thepacket engine performance data obtained from each of the packet engines,and consolidating, by the aggregator, the packet engine performance datato identify unified performance data. The unified performance data canidentify statistics for the service as managed by the appliance. Themethod can further comprise receiving, by the aggregator, a request froman agent for performance data of the appliance, and transmitting, by theaggregator, the unified performance data in response to the request.

In some embodiments, the step of collecting, by each packet engine,further comprises storing, by the aggregator, a first command in a firstlocation of memory shared by the aggregator and a first core. The firstcommand can identify a first request for packet engine statistics from afirst packet engine of the first core. The collecting can furthercomprise storing, by the aggregator, a second command in a secondlocation of memory shared by the aggregator and a second core. Thesecond command can identify a second request for packet enginestatistics from a second packet engine of the second core. The step ofstoring, by the aggregator, can further comprise reading, by theaggregator, packet engine statistical data stored by the first packetengine in the memory shared between the aggregator and first core. Thereading can be executed in response to detecting, by the aggregator, achange to a first flag in the shared memory. The storing canadditionally comprise reading, by the aggregator, packet enginestatistical data stored by the second packet engine in the memory sharedbetween the aggregator and second core. The reading can be executed inresponse to detecting, by the aggregator, a change to a second flag inthe shared memory.

In some embodiments, the step of collecting further comprisescollecting, by each packet engine, local statistics of a virtual serverof each packet engine. The virtual server can be configured to operateon the packet engine and manage the service provided by a server incommunication with the packet engine. The step of storing can furthercomprise storing to a buffer, by the aggregator, the local statistics ofeach packet engine's virtual server obtained from each of the packetengines, and the step of consolidating of the method can furthercomprise consolidating, by the aggregator, each of the local statisticsof each packet engine's virtual server to provide unified performancedata identifying statistics for the appliance as a virtual server.

In some implementations, the step of collecting further comprisescollecting, by each packet engine, a number of connections to theservice of a server as packet engine performance data, and the step ofconsolidating, by the aggregator, further comprises consolidating, bythe aggregator, the number of connections to the service from theplurality of packet engines. The aggregator can then provide a totalnumber of connections to the service from the appliance. In someinstances, the step of collecting further comprises collecting, by eachpacket engine, an average response time to the service as packet engineperformance data, and the step of consolidating further comprisesconsolidating, by the aggregator, the average response to the servicefrom the plurality of packet engines. The aggregator can provide asystem-wide average response time to the service from the appliance. Insome embodiments, the step of collecting further comprises collecting,by each packet engine, a number of bytes passed for the service aspacket engine performance data, and the step of consolidating furthercomprises consolidating, by the aggregator, the number of bytes passedfor the service from the plurality of packet engines. The aggregator canprovide a total number of bytes passed for the service from theappliance. In certain embodiments, the step of collecting furthercomprises collecting, by each packet engine, a number of differentservers providing service as packet engine performance data, and thestep of consolidating further comprises consolidating the number ofdifferent servers from the plurality of packet engines. The aggregatorcan provide a total number of distinct servers providing service managedby the appliance.

An embodiment of a method for aggregating trace data of a multi-core,multi-packet-engine appliance can comprise capturing, by each packetengine executing on a respective core of the appliance, traceinformation for network traffic received or transmitted by the packetengine, storing to a buffer, by the aggregator, the trace informationobtained from each packet engine of the plurality of packet engines, andconsolidating, by the aggregator, the trace information from each packetengine to provide unified trace data of network traffic managed by theappliance. The method for aggregating trace data can further comprisereceiving, by the aggregator, a request from an agent for network tracedata of the appliance, and transmitting, by the aggregator, the tracedata of network traffic in response to the request. In variousembodiments, the trace data may not identify the plurality of cores ofthe appliance. The agent requesting the data may not discern that theappliance comprises a plurality of cores and packet engines managingnetwork traffic. In some embodiments, the method further comprisesconverting or structuring, by the aggregator, the trace data to a formatrecognizable by the agent requesting the data.

In some embodiments, the capturing, by each packet engine, furthercomprises storing, by the aggregator, a first command in a firstlocation of memory shared with a first core. The first command canidentify a first request for trace information from a first packetengine of the first core. The step of capturing can further comprisestoring, by the aggregator, a second command in a first location ofmemory shared with a second core. The second command can identify asecond request for trace information from a second packet engine of thesecond core. The step of storing, by the aggregator, can furthercomprise reading, by the aggregator, trace information stored by thefirst packet engine in the memory shared between the aggregator and thefirst core. The reading can be executed in response to detecting achange to a first flag in the shared memory monitored by the aggregator.The step of storing can further comprise reading, by the aggregator,trace information stored by the second packet engine in the memoryshared between the aggregator and the second core. The reading can beexecuted in response to detecting a change to a second flag in theshared memory monitored by the aggregator.

In some embodiments, the step of capturing further comprises filtering,by each packet engine, trace information for network traffic, and thestep of consolidating further comprises consolidating, by theaggregator, all the filtered trace information and providing a unifiedrecord of trace information for the appliance in accordance with thefiltering. In some implementations, the step of capturing furthercomprises capturing, by each packet engine, trace information fornetwork traffic from an identified source IP address, and the step ofconsolidating further comprises consolidating, by the aggregator, allthe captured trace information and providing a unified record of networktraffic from the identified source IP address managed by the appliance.In some instances of the method, the step of capturing further comprisescapturing, by each packet engine, trace information for network trafficto an identified destination IP address, and the step of consolidatingfurther comprises consolidating, by the aggregator, all the capturedtrace information and providing a unified record of network traffic tothe identified destination IP address managed by the appliance.

The details of various embodiments of the invention are set forth in theaccompanying drawings and the description below.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and other objects, aspects, features, and advantages ofthe invention will become more apparent and better understood byreferring to the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1A is a block diagram of an embodiment of a network environment fora client to access a server via an appliance;

FIG. 1B is a block diagram of an embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIG. 1C is a block diagram of another embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIG. 1D is a block diagram of another embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIGS. 1E-1H are block diagrams of embodiments of a computing device;

FIG. 2A is a block diagram of an embodiment of an appliance forprocessing communications between a client and a server;

FIG. 2B is a block diagram of another embodiment of an appliance foroptimizing, accelerating, load-balancing and routing communicationsbetween a client and a server;

FIG. 3 is a block diagram of an embodiment of a client for communicatingwith a server via the appliance;

FIG. 4A is a block diagram of an embodiment of a virtualizationenvironment;

FIG. 4B is a block diagram of another embodiment of a virtualizationenvironment;

FIG. 4C is a block diagram of an embodiment of a virtualized appliance;

FIG. 5A are block diagrams of embodiments of approaches to implementingparallelism in a multi-core system;

FIG. 5B is a block diagram of an embodiment of a system utilizing amulti-core system;

FIG. 5C is a block diagram of another embodiment of an aspect of amulti-core system;

FIG. 6A is a block diagram of an embodiment of a system for aggregatingperformance data and trace data for a multi-core, multi-packet-engineappliance;

FIG. 6B is an embodiment of a method for aggregating performance data ortrace data for a multi-core, multi-packet-engine appliance;

FIG. 6C is an embodiment of additional steps for a method of aggregatingperformance data or trace data in a multi-core, multi-packet-engineappliance;

FIG. 6D is a block diagram of another embodiment of a system foraggregating performance data and trace data for a multi-core appliance;and

FIG. 6E is an embodiment of a method for aggregating performance dataand/or trace data for a multi-core appliance.

The features and advantages of the present invention will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings, in which like reference charactersidentify corresponding elements throughout. In the drawings, likereference numbers generally indicate identical, functionally similar,and/or structurally similar elements.

DETAILED DESCRIPTION OF THE DISCLOSURE

For purposes of reading the description of the various embodimentsbelow, the following descriptions of the sections of the specificationand their respective contents may be helpful:

-   -   Section A describes a network environment and computing        environment which may be useful for practicing embodiments        described herein;    -   Section B describes embodiments of systems and methods for        delivering a computing environment to a remote user;    -   Section C describes embodiments of systems and methods for        accelerating communications between a client and a server;    -   Section D describes embodiments of systems and methods for        virtualizing an application delivery controller;    -   Section E describes embodiments of systems and methods for        providing a multi-core architecture and environment;    -   Section F describes embodiments of systems and methods for        aggregating performance and trace data in a multi-core system;        and    -   Section G describes systems and methods for scalable multi-core        stats aggregation.

A. Network and Computing Environment

Prior to discussing the specifics of embodiments of the systems andmethods of an appliance and/or client, it may be helpful to discuss thenetwork and computing environments in which such embodiments may bedeployed. Referring now to FIG. 1A, an embodiment of a networkenvironment is depicted. In brief overview, the network environmentcomprises one or more clients 102 a-102 n (also generally referred to aslocal machine(s) 102, or client(s) 102) in communication with one ormore servers 106 a-106 n (also generally referred to as server(s) 106,or remote machine(s) 106) via one or more networks 104, 104′ (generallyreferred to as network 104). In some embodiments, a client 102communicates with a server 106 via an appliance 200.

Although FIG. 1A shows a network 104 and a network 104′ between theclients 102 and the servers 106, the clients 102 and the servers 106 maybe on the same network 104. The networks 104 and 104′ can be the sametype of network or different types of networks. The network 104 and/orthe network 104′ can be a local-area network (LAN), such as a companyIntranet, a metropolitan area network (MAN), or a wide area network(WAN), such as the Internet or the World Wide Web. In one embodiment,network 104′ may be a private network and network 104 may be a publicnetwork. In some embodiments, network 104 may be a private network andnetwork 104′ a public network. In another embodiment, networks 104 and104′ may both be private networks. In some embodiments, clients 102 maybe located at a branch office of a corporate enterprise communicatingvia a WAN connection over the network 104 to the servers 106 located ata corporate data center.

The network 104 and/or 104′ be any type and/or form of network and mayinclude any of the following: a point to point network, a broadcastnetwork, a wide area network, a local area network, a telecommunicationsnetwork, a data communication network, a computer network, an ATM(Asynchronous Transfer Mode) network, a SONET (Synchronous OpticalNetwork) network, a SDH (Synchronous Digital Hierarchy) network, awireless network and a wireline network. In some embodiments, thenetwork 104 may comprise a wireless link, such as an infrared channel orsatellite band. The topology of the network 104 and/or 104′ may be abus, star, or ring network topology. The network 104 and/or 104′ andnetwork topology may be of any such network or network topology as knownto those ordinarily skilled in the art capable of supporting theoperations described herein.

As shown in FIG. 1A, the appliance 200, which also may be referred to asan interface unit 200 or gateway 200, is shown between the networks 104and 104′. In some embodiments, the appliance 200 may be located onnetwork 104. For example, a branch office of a corporate enterprise maydeploy an appliance 200 at the branch office. In other embodiments, theappliance 200 may be located on network 104′. For example, an appliance200 may be located at a corporate data center. In yet anotherembodiment, a plurality of appliances 200 may be deployed on network104. In some embodiments, a plurality of appliances 200 may be deployedon network 104′. In one embodiment, a first appliance 200 communicateswith a second appliance 200′. In other embodiments, the appliance 200could be a part of any client 102 or server 106 on the same or differentnetwork 104,104′ as the client 102. One or more appliances 200 may belocated at any point in the network or network communications pathbetween a client 102 and a server 106.

In some embodiments, the appliance 200 comprises any of the networkdevices manufactured by Citrix Systems, Inc. of Ft. Lauderdale Fla.,referred to as Citrix NetScaler devices. In other embodiments, theappliance 200 includes any of the product embodiments referred to asWebAccelerator and BigIP manufactured by F5 Networks, Inc. of Seattle,Wash. In another embodiment, the appliance 205 includes any of the DXacceleration device platforms and/or the SSL VPN series of devices, suchas SA 700, SA 2000, SA 4000, and SA 6000 devices manufactured by JuniperNetworks, Inc. of Sunnyvale, Calif. In yet another embodiment, theappliance 200 includes any application acceleration and/or securityrelated appliances and/or software manufactured by Cisco Systems, Inc.of San Jose, Calif., such as the Cisco ACE Application Control EngineModule service software and network modules, and Cisco AVS SeriesApplication Velocity System.

In one embodiment, the system may include multiple, logically-groupedservers 106. In these embodiments, the logical group of servers may bereferred to as a server farm 38. In some of these embodiments, theserves 106 may be geographically dispersed. In some cases, a farm 38 maybe administered as a single entity. In other embodiments, the serverfarm 38 comprises a plurality of server farms 38. In one embodiment, theserver farm executes one or more applications on behalf of one or moreclients 102.

The servers 106 within each farm 38 can be heterogeneous. One or more ofthe servers 106 can operate according to one type of operating systemplatform (e.g., WINDOWS NT, manufactured by Microsoft Corp. of Redmond,Wash.), while one or more of the other servers 106 can operate onaccording to another type of operating system platform (e.g., Unix orLinux). The servers 106 of each farm 38 do not need to be physicallyproximate to another server 106 in the same farm 38. Thus, the group ofservers 106 logically grouped as a farm 38 may be interconnected using awide-area network (WAN) connection or medium-area network (MAN)connection. For example, a farm 38 may include servers 106 physicallylocated in different continents or different regions of a continent,country, state, city, campus, or room. Data transmission speeds betweenservers 106 in the farm 38 can be increased if the servers 106 areconnected using a local-area network (LAN) connection or some form ofdirect connection.

Servers 106 may be referred to as a file server, application server, webserver, proxy server, or gateway server. In some embodiments, a server106 may have the capacity to function as either an application server oras a master application server. In one embodiment, a server 106 mayinclude an Active Directory. The clients 102 may also be referred to asclient nodes or endpoints. In some embodiments, a client 102 has thecapacity to function as both a client node seeking access toapplications on a server and as an application server providing accessto hosted applications for other clients 102 a-102 n.

In some embodiments, a client 102 communicates with a server 106. In oneembodiment, the client 102 communicates directly with one of the servers106 in a farm 38. In another embodiment, the client 102 executes aprogram neighborhood application to communicate with a server 106 in afarm 38. In still another embodiment, the server 106 provides thefunctionality of a master node. In some embodiments, the client 102communicates with the server 106 in the farm 38 through a network 104.Over the network 104, the client 102 can, for example, request executionof various applications hosted by the servers 106 a-106 n in the farm 38and receive output of the results of the application execution fordisplay. In some embodiments, only the master node provides thefunctionality required to identify and provide address informationassociated with a server 106′ hosting a requested application.

In one embodiment, the server 106 provides functionality of a webserver. In another embodiment, the server 106 a receives requests fromthe client 102, forwards the requests to a second server 106 b andresponds to the request by the client 102 with a response to the requestfrom the server 106 b. In still another embodiment, the server 106acquires an enumeration of applications available to the client 102 andaddress information associated with a server 106 hosting an applicationidentified by the enumeration of applications. In yet anotherembodiment, the server 106 presents the response to the request to theclient 102 using a web interface. In one embodiment, the client 102communicates directly with the server 106 to access the identifiedapplication. In another embodiment, the client 102 receives applicationoutput data, such as display data, generated by an execution of theidentified application on the server 106.

Referring now to FIG. 1B, an embodiment of a network environmentdeploying multiple appliances 200 is depicted. A first appliance 200 maybe deployed on a first network 104 and a second appliance 200′ on asecond network 104′. For example a corporate enterprise may deploy afirst appliance 200 at a branch office and a second appliance 200′ at adata center. In another embodiment, the first appliance 200 and secondappliance 200′ are deployed on the same network 104 or network 104. Forexample, a first appliance 200 may be deployed for a first server farm38, and a second appliance 200 may be deployed for a second server farm38′. In another example, a first appliance 200 may be deployed at afirst branch office while the second appliance 200′ is deployed at asecond branch office'. In some embodiments, the first appliance 200 andsecond appliance 200′ work in cooperation or in conjunction with eachother to accelerate network traffic or the delivery of application anddata between a client and a server

Referring now to FIG. 1C, another embodiment of a network environmentdeploying the appliance 200 with one or more other types of appliances,such as between one or more WAN optimization appliance 205, 205′ isdepicted. For example a first WAN optimization appliance 205 is shownbetween networks 104 and 104′ and a second WAN optimization appliance205′ may be deployed between the appliance 200 and one or more servers106. By way of example, a corporate enterprise may deploy a first WANoptimization appliance 205 at a branch office and a second WANoptimization appliance 205′ at a data center. In some embodiments, theappliance 205 may be located on network 104′. In other embodiments, theappliance 205′ may be located on network 104. In some embodiments, theappliance 205′ may be located on network 104′ or network 104″. In oneembodiment, the appliance 205 and 205′ are on the same network. Inanother embodiment, the appliance 205 and 205′ are on differentnetworks. In another example, a first WAN optimization appliance 205 maybe deployed for a first server farm 38 and a second WAN optimizationappliance 205′ for a second server farm 38′

In one embodiment, the appliance 205 is a device for accelerating,optimizing or otherwise improving the performance, operation, or qualityof service of any type and form of network traffic, such as traffic toand/or from a WAN connection. In some embodiments, the appliance 205 isa performance enhancing proxy. In other embodiments, the appliance 205is any type and form of WAN optimization or acceleration device,sometimes also referred to as a WAN optimization controller. In oneembodiment, the appliance 205 is any of the product embodiments referredto as WANScaler manufactured by Citrix Systems, Inc. of Ft. Lauderdale,Fla. In other embodiments, the appliance 205 includes any of the productembodiments referred to as BIG-IP link controller and WANjetmanufactured by F5 Networks, Inc. of Seattle, Wash. In anotherembodiment, the appliance 205 includes any of the WX and WXC WANacceleration device platforms manufactured by Juniper Networks, Inc. ofSunnyvale, Calif. In some embodiments, the appliance 205 includes any ofthe steelhead line of WAN optimization appliances manufactured byRiverbed Technology of San Francisco, Calif. In other embodiments, theappliance 205 includes any of the WAN related devices manufactured byExpand Networks Inc. of Roseland, N.J. In one embodiment, the appliance205 includes any of the WAN related appliances manufactured by PacketeerInc. of Cupertino, Calif., such as the PacketShaper, iShared, and SkyXproduct embodiments provided by Packeteer. In yet another embodiment,the appliance 205 includes any WAN related appliances and/or softwaremanufactured by Cisco Systems, Inc. of San Jose, Calif., such as theCisco Wide Area Network Application Services software and networkmodules, and Wide Area Network engine appliances.

In one embodiment, the appliance 205 provides application and dataacceleration services for branch-office or remote offices. In oneembodiment, the appliance 205 includes optimization of Wide Area FileServices (WAFS). In another embodiment, the appliance 205 acceleratesthe delivery of files, such as via the Common Internet File System(CIFS) protocol. In other embodiments, the appliance 205 providescaching in memory and/or storage to accelerate delivery of applicationsand data. In one embodiment, the appliance 205 provides compression ofnetwork traffic at any level of the network stack or at any protocol ornetwork layer. In another embodiment, the appliance 205 providestransport layer protocol optimizations, flow control, performanceenhancements or modifications and/or management to accelerate deliveryof applications and data over a WAN connection. For example, in oneembodiment, the appliance 205 provides Transport Control Protocol (TCP)optimizations. In other embodiments, the appliance 205 providesoptimizations, flow control, performance enhancements or modificationsand/or management for any session or application layer protocol.

In another embodiment, the appliance 205 encoded any type and form ofdata or information into custom or standard TCP and/or IP header fieldsor option fields of network packet to announce presence, functionalityor capability to another appliance 205′. In another embodiment, anappliance 205′ may communicate with another appliance 205′ using dataencoded in both TCP and/or IP header fields or options. For example, theappliance may use TCP option(s) or IP header fields or options tocommunicate one or more parameters to be used by the appliances 205,205′ in performing functionality, such as WAN acceleration, or forworking in conjunction with each other.

In some embodiments, the appliance 200 preserves any of the informationencoded in TCP and/or IP header and/or option fields communicatedbetween appliances 205 and 205′. For example, the appliance 200 mayterminate a transport layer connection traversing the appliance 200,such as a transport layer connection from between a client and a servertraversing appliances 205 and 205′. In one embodiment, the appliance 200identifies and preserves any encoded information in a transport layerpacket transmitted by a first appliance 205 via a first transport layerconnection and communicates a transport layer packet with the encodedinformation to a second appliance 205′ via a second transport layerconnection.

Referring now to FIG. 1D, a network environment for delivering and/oroperating a computing environment on a client 102 is depicted. In someembodiments, a server 106 includes an application delivery system 190for delivering a computing environment or an application and/or datafile to one or more clients 102. In brief overview, a client 10 is incommunication with a server 106 via network 104, 104′ and appliance 200.For example, the client 102 may reside in a remote office of a company,e.g., a branch office, and the server 106 may reside at a corporate datacenter. The client 102 comprises a client agent 120, and a computingenvironment 15. The computing environment 15 may execute or operate anapplication that accesses, processes or uses a data file. The computingenvironment 15, application and/or data file may be delivered via theappliance 200 and/or the server 106.

In some embodiments, the appliance 200 accelerates delivery of acomputing environment 15, or any portion thereof, to a client 102. Inone embodiment, the appliance 200 accelerates the delivery of thecomputing environment 15 by the application delivery system 190. Forexample, the embodiments described herein may be used to acceleratedelivery of a streaming application and data file processable by theapplication from a central corporate data center to a remote userlocation, such as a branch office of the company. In another embodiment,the appliance 200 accelerates transport layer traffic between a client102 and a server 106. The appliance 200 may provide accelerationtechniques for accelerating any transport layer payload from a server106 to a client 102, such as: 1) transport layer connection pooling, 2)transport layer connection multiplexing, 3) transport control protocolbuffering, 4) compression and 5) caching. In some embodiments, theappliance 200 provides load balancing of servers 106 in responding torequests from clients 102. In other embodiments, the appliance 200 actsas a proxy or access server to provide access to the one or more servers106. In another embodiment, the appliance 200 provides a secure virtualprivate network connection from a first network 104 of the client 102 tothe second network 104′ of the server 106, such as an SSL VPNconnection. It yet other embodiments, the appliance 200 providesapplication firewall security, control and management of the connectionand communications between a client 102 and a server 106.

In some embodiments, the application delivery management system 190provides application delivery techniques to deliver a computingenvironment to a desktop of a user, remote or otherwise, based on aplurality of execution methods and based on any authentication andauthorization policies applied via a policy engine 195. With thesetechniques, a remote user may obtain a computing environment and accessto server stored applications and data files from any network connecteddevice 100. In one embodiment, the application delivery system 190 mayreside or execute on a server 106. In another embodiment, theapplication delivery system 190 may reside or execute on a plurality ofservers 106 a-106 n. In some embodiments, the application deliverysystem 190 may execute in a server farm 38. In one embodiment, theserver 106 executing the application delivery system 190 may also storeor provide the application and data file. In another embodiment, a firstset of one or more servers 106 may execute the application deliverysystem 190, and a different server 106 n may store or provide theapplication and data file. In some embodiments, each of the applicationdelivery system 190, the application, and data file may reside or belocated on different servers. In yet another embodiment, any portion ofthe application delivery system 190 may reside, execute or be stored onor distributed to the appliance 200, or a plurality of appliances.

The client 102 may include a computing environment 15 for executing anapplication that uses or processes a data file. The client 102 vianetworks 104, 104′ and appliance 200 may request an application and datafile from the server 106. In one embodiment, the appliance 200 mayforward a request from the client 102 to the server 106. For example,the client 102 may not have the application and data file stored oraccessible locally. In response to the request, the application deliverysystem 190 and/or server 106 may deliver the application and data fileto the client 102. For example, in one embodiment, the server 106 maytransmit the application as an application stream to operate incomputing environment 15 on client 102.

In some embodiments, the application delivery system 190 comprises anyportion of the Citrix Access Suite™ by Citrix Systems, Inc., such as theMetaFrame or Citrix Presentation Server™ and/or any of the Microsoft®Windows Terminal Services manufactured by the Microsoft Corporation. Inone embodiment, the application delivery system 190 may deliver one ormore applications to clients 102 or users via a remote-display protocolor otherwise via remote-based or server-based computing. In anotherembodiment, the application delivery system 190 may deliver one or moreapplications to clients or users via steaming of the application.

In one embodiment, the application delivery system 190 includes a policyengine 195 for controlling and managing the access to, selection ofapplication execution methods and the delivery of applications. In someembodiments, the policy engine 195 determines the one or moreapplications a user or client 102 may access. In another embodiment, thepolicy engine 195 determines how the application should be delivered tothe user or client 102, e.g., the method of execution. In someembodiments, the application delivery system 190 provides a plurality ofdelivery techniques from which to select a method of applicationexecution, such as a server-based computing, streaming or delivering theapplication locally to the client 120 for local execution.

In one embodiment, a client 102 requests execution of an applicationprogram and the application delivery system 190 comprising a server 106selects a method of executing the application program. In someembodiments, the server 106 receives credentials from the client 102. Inanother embodiment, the server 106 receives a request for an enumerationof available applications from the client 102. In one embodiment, inresponse to the request or receipt of credentials, the applicationdelivery system 190 enumerates a plurality of application programsavailable to the client 102. The application delivery system 190receives a request to execute an enumerated application. The applicationdelivery system 190 selects one of a predetermined number of methods forexecuting the enumerated application, for example, responsive to apolicy of a policy engine. The application delivery system 190 mayselect a method of execution of the application enabling the client 102to receive application-output data generated by execution of theapplication program on a server 106. The application delivery system 190may select a method of execution of the application enabling the localmachine 10 to execute the application program locally after retrieving aplurality of application files comprising the application. In yetanother embodiment, the application delivery system 190 may select amethod of execution of the application to stream the application via thenetwork 104 to the client 102.

A client 102 may execute, operate or otherwise provide an application,which can be any type and/or form of software, program, or executableinstructions such as any type and/or form of web browser, web-basedclient, client-server application, a thin-client computing client, anActiveX control, or a Java applet, or any other type and/or form ofexecutable instructions capable of executing on client 102. In someembodiments, the application may be a server-based or a remote-basedapplication executed on behalf of the client 102 on a server 106. In oneembodiments the server 106 may display output to the client 102 usingany thin-client or remote-display protocol, such as the IndependentComputing Architecture (ICA) protocol manufactured by Citrix Systems,Inc. of Ft. Lauderdale, Fla. or the Remote Desktop Protocol (RDP)manufactured by the Microsoft Corporation of Redmond, Wash. Theapplication can use any type of protocol and it can be, for example, anHTTP client, an FTP client, an Oscar client, or a Telnet client. Inother embodiments, the application comprises any type of softwarerelated to VoIP communications, such as a soft IP telephone. In furtherembodiments, the application comprises any application related toreal-time data communications, such as applications for streaming videoand/or audio.

In some embodiments, the server 106 or a server farm 38 may be runningone or more applications, such as an application providing a thin-clientcomputing or remote display presentation application. In one embodiment,the server 106 or server farm 38 executes as an application, any portionof the Citrix Access Suite™ by Citrix Systems, Inc., such as theMetaFrame or Citrix Presentation Server™, and/or any of the Microsoft®Windows Terminal Services manufactured by the Microsoft Corporation. Inone embodiment, the application is an ICA client, developed by CitrixSystems, Inc. of Fort Lauderdale, Fla. In other embodiments, theapplication includes a Remote Desktop (RDP) client, developed byMicrosoft Corporation of Redmond, Wash. Also, the server 106 may run anapplication, which for example, may be an application server providingemail services such as Microsoft Exchange manufactured by the MicrosoftCorporation of Redmond, Wash., a web or Internet server, or a desktopsharing server, or a collaboration server. In some embodiments, any ofthe applications may comprise any type of hosted service or products,such as GoToMeeting™ provided by Citrix Online Division, Inc. of SantaBarbara, Calif., WebEx™ provided by WebEx, Inc. of Santa Clara, Calif.,or Microsoft Office Live Meeting provided by Microsoft Corporation ofRedmond, Wash.

Still referring to FIG. 1D, an embodiment of the network environment mayinclude a monitoring server 106A. The monitoring server 106A may includeany type and form performance monitoring service 198. The performancemonitoring service 198 may include monitoring, measurement and/ormanagement software and/or hardware, including data collection,aggregation, analysis, management and reporting. In one embodiment, theperformance monitoring service 198 includes one or more monitoringagents 197. The monitoring agent 197 includes any software, hardware orcombination thereof for performing monitoring, measurement and datacollection activities on a device, such as a client 102, server 106 oran appliance 200, 205. In some embodiments, the monitoring agent 197includes any type and form of script, such as Visual Basic script, orJavascript. In one embodiment, the monitoring agent 197 executestransparently to any application and/or user of the device. In someembodiments, the monitoring agent 197 is installed and operatedunobtrusively to the application or client. In yet another embodiment,the monitoring agent 197 is installed and operated without anyinstrumentation for the application or device.

In some embodiments, the monitoring agent 197 monitors, measures andcollects data on a predetermined frequency. In other embodiments, themonitoring agent 197 monitors, measures and collects data based upondetection of any type and form of event. For example, the monitoringagent 197 may collect data upon detection of a request for a web page orreceipt of an HTTP response. In another example, the monitoring agent197 may collect data upon detection of any user input events, such as amouse click. The monitoring agent 197 may report or provide anymonitored, measured or collected data to the monitoring service 198. Inone embodiment, the monitoring agent 197 transmits information to themonitoring service 198 according to a schedule or a predeterminedfrequency. In another embodiment, the monitoring agent 197 transmitsinformation to the monitoring service 198 upon detection of an event.

In some embodiments, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of any networkresource or network infrastructure element, such as a client, server,server farm, appliance 200, appliance 205, or network connection. In oneembodiment, the monitoring service 198 and/or monitoring agent 197performs monitoring and performance measurement of any transport layerconnection, such as a TCP or UDP connection. In another embodiment, themonitoring service 198 and/or monitoring agent 197 monitors and measuresnetwork latency. In yet one embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures bandwidth utilization.

In other embodiments, the monitoring service 198 and/or monitoring agent197 monitors and measures end-user response times. In some embodiments,the monitoring service 198 performs monitoring and performancemeasurement of an application. In another embodiment, the monitoringservice 198 and/or monitoring agent 197 performs monitoring andperformance measurement of any session or connection to the application.In one embodiment, the monitoring service 198 and/or monitoring agent197 monitors and measures performance of a browser. In anotherembodiment, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of HTTP based transactions. In someembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of a Voice over IP (VoIP) applicationor session. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors and measures performance of a remotedisplay protocol application, such as an ICA client or RDP client. Inyet another embodiment, the monitoring service 198 and/or monitoringagent 197 monitors and measures performance of any type and form ofstreaming media. In still a further embodiment, the monitoring service198 and/or monitoring agent 197 monitors and measures performance of ahosted application or a Software-As-A-Service (SaaS) delivery model.

In some embodiments, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of one or moretransactions, requests or responses related to application. In otherembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures any portion of an application layer stack, such asany .NET or J2EE calls. In one embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures database or SQLtransactions. In yet another embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures any method, functionor application programming interface (API) call.

In one embodiment, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of a delivery ofapplication and/or data from a server to a client via one or moreappliances, such as appliance 200 and/or appliance 205. In someembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of delivery of a virtualizedapplication. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors and measures performance of delivery of astreaming application. In another embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures performance ofdelivery of a desktop application to a client and/or the execution ofthe desktop application on the client. In another embodiment, themonitoring service 198 and/or monitoring agent 197 monitors and measuresperformance of a client/server application.

In one embodiment, the monitoring service 198 and/or monitoring agent197 is designed and constructed to provide application performancemanagement for the application delivery system 190. For example, themonitoring service 198 and/or monitoring agent 197 may monitor, measureand manage the performance of the delivery of applications via theCitrix Presentation Server. In this example, the monitoring service 198and/or monitoring agent 197 monitors individual ICA sessions. Themonitoring service 198 and/or monitoring agent 197 may measure the totaland per session system resource usage, as well as application andnetworking performance. The monitoring service 198 and/or monitoringagent 197 may identify the active servers for a given user and/or usersession. In some embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors back-end connections between theapplication delivery system 190 and an application and/or databaseserver. The monitoring service 198 and/or monitoring agent 197 maymeasure network latency, delay and volume per user-session or ICAsession.

In some embodiments, the monitoring service 198 and/or monitoring agent197 measures and monitors memory usage for the application deliverysystem 190, such as total memory usage, per user session and/or perprocess. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 measures and monitors CPU usage the applicationdelivery system 190, such as total CPU usage, per user session and/orper process. In another embodiments, the monitoring service 198 and/ormonitoring agent 197 measures and monitors the time required to log-into an application, a server, or the application delivery system, such asCitrix Presentation Server. In one embodiment, the monitoring service198 and/or monitoring agent 197 measures and monitors the duration auser is logged into an application, a server, or the applicationdelivery system 190. In some embodiments, the monitoring service 198and/or monitoring agent 197 measures and monitors active and inactivesession counts for an application, server or application delivery systemsession. In yet another embodiment, the monitoring service 198 and/ormonitoring agent 197 measures and monitors user session latency.

In yet further embodiments, the monitoring service 198 and/or monitoringagent 197 measures and monitors measures and monitors any type and formof server metrics. In one embodiment, the monitoring service 198 and/ormonitoring agent 197 measures and monitors metrics related to systemmemory, CPU usage, and disk storage. In another embodiment, themonitoring service 198 and/or monitoring agent 197 measures and monitorsmetrics related to page faults, such as page faults per second. In otherembodiments, the monitoring service 198 and/or monitoring agent 197measures and monitors round-trip time metrics. In yet anotherembodiment, the monitoring service 198 and/or monitoring agent 197measures and monitors metrics related to application crashes, errorsand/or hangs.

In some embodiments, the monitoring service 198 and monitoring agent 198includes any of the product embodiments referred to as EdgeSightmanufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. In anotherembodiment, the performance monitoring service 198 and/or monitoringagent 198 includes any portion of the product embodiments referred to asthe TrueView product suite manufactured by the Symphoniq Corporation ofPalo Alto, Calif. In one embodiment, the performance monitoring service198 and/or monitoring agent 198 includes any portion of the productembodiments referred to as the TeaLeaf CX product suite manufactured bythe TeaLeaf Technology Inc. of San Francisco, Calif. In otherembodiments, the performance monitoring service 198 and/or monitoringagent 198 includes any portion of the business service managementproducts, such as the BMC Performance Manager and Patrol products,manufactured by BMC Software, Inc. of Houston, Tex.

The client 102, server 106, and appliance 200 may be deployed as and/orexecuted on any type and form of computing device, such as a computer,network device or appliance capable of communicating on any type andform of network and performing the operations described herein. FIGS. 1Eand 1F depict block diagrams of a computing device 100 useful forpracticing an embodiment of the client 102, server 106 or appliance 200.As shown in FIGS. 1E and 1F, each computing device 100 includes acentral processing unit 101, and a main memory unit 122. As shown inFIG. 1E, a computing device 100 may include a visual display device 124,a keyboard 126 and/or a pointing device 127, such as a mouse. Eachcomputing device 100 may also include additional optional elements, suchas one or more input/output devices 130 a-130 b (generally referred tousing reference numeral 130), and a cache memory 140 in communicationwith the central processing unit 101.

The central processing unit 101 is any logic circuitry that responds toand processes instructions fetched from the main memory unit 122. Inmany embodiments, the central processing unit is provided by amicroprocessor unit, such as: those manufactured by Intel Corporation ofMountain View, Calif.; those manufactured by Motorola Corporation ofSchaumburg, Ill.; those manufactured by Transmeta Corporation of SantaClara, Calif.; the RS/6000 processor, those manufactured byInternational Business Machines of White Plains, N.Y.; or thosemanufactured by Advanced Micro Devices of Sunnyvale, Calif. Thecomputing device 100 may be based on any of these processors, or anyother processor capable of operating as described herein.

Main memory unit 122 may be one or more memory chips capable of storingdata and allowing any storage location to be directly accessed by themicroprocessor 101, such as Static random access memory (SRAM), BurstSRAM or SynchBurst SRAM (BSRAM), Dynamic random access memory (DRAM),Fast Page Mode DRAM (FPM DRAM), Enhanced DRAM (EDRAM), Extended DataOutput RAM (EDO RAM), Extended Data Output DRAM (EDO DRAM), BurstExtended Data Output DRAM (BEDO DRAM), Enhanced DRAM (EDRAM),synchronous DRAM (SDRAM), JEDEC SRAM, PC100 SDRAM, Double Data RateSDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), SyncLink DRAM (SLDRAM),Direct Rambus DRAM (DRDRAM), or Ferroelectric RAM (FRAM). The mainmemory 122 may be based on any of the above described memory chips, orany other available memory chips capable of operating as describedherein. In the embodiment shown in FIG. 1E, the processor 101communicates with main memory 122 via a system bus 150 (described inmore detail below). FIG. 1F depicts an embodiment of a computing device100 in which the processor communicates directly with main memory 122via a memory port 103. For example, in FIG. 1F the main memory 122 maybe DRDRAM.

FIG. 1F depicts an embodiment in which the main processor 101communicates directly with cache memory 140 via a secondary bus,sometimes referred to as a backside bus. In other embodiments, the mainprocessor 101 communicates with cache memory 140 using the system bus150. Cache memory 140 typically has a faster response time than mainmemory 122 and is typically provided by SRAM, BSRAM, or EDRAM. In theembodiment shown in FIG. 1F, the processor 101 communicates with variousI/O devices 130 via a local system bus 150. Various busses may be usedto connect the central processing unit 101 to any of the I/O devices130, including a VESA VL bus, an ISA bus, an EISA bus, a MicroChannelArchitecture (MCA) bus, a PCI bus, a PCI-X bus, a PCI-Express bus, or aNuBus. For embodiments in which the I/O device is a video display 124,the processor 101 may use an Advanced Graphics Port (AGP) to communicatewith the display 124. FIG. 1F depicts an embodiment of a computer 100 inwhich the main processor 101 communicates directly with I/O device 130 bvia HyperTransport, Rapid I/O, or InfiniBand. FIG. 1F also depicts anembodiment in which local busses and direct communication are mixed: theprocessor 101 communicates with I/O device 130 b using a localinterconnect bus while communicating with I/O device 130 a directly.

The computing device 100 may support any suitable installation device116, such as a floppy disk drive for receiving floppy disks such as3.5-inch, 5.25-inch disks or ZIP disks, a CD-ROM drive, a CD-R/RW drive,a DVD-ROM drive, tape drives of various formats, USB device, hard-driveor any other device suitable for installing software and programs suchas any client agent 120, or portion thereof. The computing device 100may further comprise a storage device 128, such as one or more hard diskdrives or redundant arrays of independent disks, for storing anoperating system and other related software, and for storing applicationsoftware programs such as any program related to the client agent 120.Optionally, any of the installation devices 116 could also be used asthe storage device 128. Additionally, the operating system and thesoftware can be run from a bootable medium, for example, a bootable CD,such as KNOPPIX®, a bootable CD for GNU/Linux that is available as aGNU/Linux distribution from knoppix.net.

Furthermore, the computing device 100 may include a network interface118 to interface to a Local Area Network (LAN), Wide Area Network (WAN)or the Internet through a variety of connections including, but notlimited to, standard telephone lines, LAN or WAN links (e.g., 802.11,T1, T3, 56 kb, X.25), broadband connections (e.g., ISDN, Frame Relay,ATM), wireless connections, or some combination of any or all of theabove. The network interface 118 may comprise a built-in networkadapter, network interface card, PCMCIA network card, card bus networkadapter, wireless network adapter, USB network adapter, modem or anyother device suitable for interfacing the computing device 100 to anytype of network capable of communication and performing the operationsdescribed herein. A wide variety of I/O devices 130 a-130 n may bepresent in the computing device 100. Input devices include keyboards,mice, trackpads, trackballs, microphones, and drawing tablets. Outputdevices include video displays, speakers, inkjet printers, laserprinters, and dye-sublimation printers. The I/O devices 130 may becontrolled by an I/O controller 123 as shown in FIG. 1E. The I/Ocontroller may control one or more I/O devices such as a keyboard 126and a pointing device 127, e.g., a mouse or optical pen. Furthermore, anI/O device may also provide storage 128 and/or an installation medium116 for the computing device 100. In still other embodiments, thecomputing device 100 may provide USB connections to receive handheld USBstorage devices such as the USB Flash Drive line of devices manufacturedby Twintech Industry, Inc. of Los Alamitos, Calif.

In some embodiments, the computing device 100 may comprise or beconnected to multiple display devices 124 a-124 n, which each may be ofthe same or different type and/or form. As such, any of the I/O devices130 a-130 n and/or the I/O controller 123 may comprise any type and/orform of suitable hardware, software, or combination of hardware andsoftware to support, enable or provide for the connection and use ofmultiple display devices 124 a-124 n by the computing device 100. Forexample, the computing device 100 may include any type and/or form ofvideo adapter, video card, driver, and/or library to interface,communicate, connect or otherwise use the display devices 124 a-124 n.In one embodiment, a video adapter may comprise multiple connectors tointerface to multiple display devices 124 a-124 n. In other embodiments,the computing device 100 may include multiple video adapters, with eachvideo adapter connected to one or more of the display devices 124 a-124n. In some embodiments, any portion of the operating system of thecomputing device 100 may be configured for using multiple displays 124a-124 n. In other embodiments, one or more of the display devices 124a-124 n may be provided by one or more other computing devices, such ascomputing devices 100 a and 100 b connected to the computing device 100,for example, via a network. These embodiments may include any type ofsoftware designed and constructed to use another computer's displaydevice as a second display device 124 a for the computing device 100.One ordinarily skilled in the art will recognize and appreciate thevarious ways and embodiments that a computing device 100 may beconfigured to have multiple display devices 124 a-124 n.

In further embodiments, an I/O device 130 may be a bridge 170 betweenthe system bus 150 and an external communication bus, such as a USB bus,an Apple Desktop Bus, an RS-232 serial connection, a SCSI bus, aFireWire bus, a FireWire 800 bus, an Ethernet bus, an AppleTalk bus, aGigabit Ethernet bus, an Asynchronous Transfer Mode bus, a HIPPI bus, aSuper HIPPI bus, a SerialPlus bus, a SCI/LAMP bus, a FibreChannel bus,or a Serial Attached small computer system interface bus.

A computing device 100 of the sort depicted in FIGS. 1E and 1F typicallyoperate under the control of operating systems, which control schedulingof tasks and access to system resources. The computing device 100 can berunning any operating system such as any of the versions of theMicrosoft® Windows operating systems, the different releases of the Unixand Linux operating systems, any version of the Mac OS® for Macintoshcomputers, any embedded operating system, any real-time operatingsystem, any open source operating system, any proprietary operatingsystem, any operating systems for mobile computing devices, or any otheroperating system capable of running on the computing device andperforming the operations described herein. Typical operating systemsinclude: WINDOWS 3.x, WINDOWS 95, WINDOWS 98, WINDOWS 2000, WINDOWS NT3.51, WINDOWS NT 4.0, WINDOWS CE, and WINDOWS XP, all of which aremanufactured by Microsoft Corporation of Redmond, Wash.; MacOS,manufactured by Apple Computer of Cupertino, California; OS/2,manufactured by International Business Machines of Armonk, N.Y.; andLinux, a freely-available operating system distributed by Caldera Corp.of Salt Lake City, Utah, or any type and/or form of a Unix operatingsystem, among others.

In other embodiments, the computing device 100 may have differentprocessors, operating systems, and input devices consistent with thedevice. For example, in one embodiment the computer 100 is a Treo 180,270, 1060, 600 or 650 smart phone manufactured by Palm, Inc. In thisembodiment, the Treo smart phone is operated under the control of thePalmOS operating system and includes a stylus input device as well as afive-way navigator device. Moreover, the computing device 100 can be anyworkstation, desktop computer, laptop or notebook computer, server,handheld computer, mobile telephone, any other computer, or other formof computing or telecommunications device that is capable ofcommunication and that has sufficient processor power and memorycapacity to perform the operations described herein.

As shown in FIG. 1G, the computing device 100 may comprise multipleprocessors and may provide functionality for simultaneous execution ofinstructions or for simultaneous execution of one instruction on morethan one piece of data. In some embodiments, the computing device 100may comprise a parallel processor with one or more cores. In one ofthese embodiments, the computing device 100 is a shared memory paralleldevice, with multiple processors and/or multiple processor cores,accessing all available memory as a single global address space. Inanother of these embodiments, the computing device 100 is a distributedmemory parallel device with multiple processors each accessing localmemory only. In still another of these embodiments, the computing device100 has both some memory which is shared and some memory which can onlybe accessed by particular processors or subsets of processors. In stilleven another of these embodiments, the computing device 100, such as amulti-core microprocessor, combines two or more independent processorsinto a single package, often a single integrated circuit (IC). In yetanother of these embodiments, the computing device 100 includes a chiphaving a CELL BROADBAND ENGINE architecture and including a Powerprocessor element and a plurality of synergistic processing elements,the Power processor element and the plurality of synergistic processingelements linked together by an internal high speed bus, which may bereferred to as an element interconnect bus.

In some embodiments, the processors provide functionality for executionof a single instruction simultaneously on multiple pieces of data(SIMD). In other embodiments, the processors provide functionality forexecution of multiple instructions simultaneously on multiple pieces ofdata (MIMD). In still other embodiments, the processor may use anycombination of SIMD and MIMD cores in a single device.

In some embodiments, the computing device 100 may comprise a graphicsprocessing unit. In one of these embodiments, depicted in FIG. 1H, thecomputing device 100 includes at least one central processing unit 101and at least one graphics processing unit. In another of theseembodiments, the computing device 100 includes at least one parallelprocessing unit and at least one graphics processing unit. In stillanother of these embodiments, the computing device 100 includes aplurality of processing units of any type, one of the plurality ofprocessing units comprising a graphics processing unit.

In some embodiments, a first computing device 100 a executes anapplication on behalf of a user of a client computing device 100 b. Inother embodiments, a computing device 100 a executes a virtual machine,which provides an execution session within which applications execute onbehalf of a user or a client computing devices 100 b. In one of theseembodiments, the execution session is a hosted desktop session. Inanother of these embodiments, the computing device 100 executes aterminal services session. The terminal services session may provide ahosted desktop environment. In still another of these embodiments, theexecution session provides access to a computing environment, which maycomprise one or more of: an application, a plurality of applications, adesktop application, and a desktop session in which one or moreapplications may execute.

B. Appliance Architecture

FIG. 2A illustrates an example embodiment of the appliance 200. Thearchitecture of the appliance 200 in FIG. 2A is provided by way ofillustration only and is not intended to be limiting. As shown in FIG.2, appliance 200 comprises a hardware layer 206 and a software layerdivided into a user space 202 and a kernel space 204.

Hardware layer 206 provides the hardware elements upon which programsand services within kernel space 204 and user space 202 are executed.Hardware layer 206 also provides the structures and elements which allowprograms and services within kernel space 204 and user space 202 tocommunicate data both internally and externally with respect toappliance 200. As shown in FIG. 2, the hardware layer 206 includes aprocessing unit 262 for executing software programs and services, amemory 264 for storing software and data, network ports 266 fortransmitting and receiving data over a network, and an encryptionprocessor 260 for performing functions related to Secure Sockets Layerprocessing of data transmitted and received over the network. In someembodiments, the central processing unit 262 may perform the functionsof the encryption processor 260 in a single processor. Additionally, thehardware layer 206 may comprise multiple processors for each of theprocessing unit 262 and the encryption processor 260. The processor 262may include any of the processors 101 described above in connection withFIGS. 1E and 1F. For example, in one embodiment, the appliance 200comprises a first processor 262 and a second processor 262′. In otherembodiments, the processor 262 or 262′ comprises a multi-core processor.

Although the hardware layer 206 of appliance 200 is generallyillustrated with an encryption processor 260, processor 260 may be aprocessor for performing functions related to any encryption protocol,such as the Secure Socket Layer (SSL) or Transport Layer Security (TLS)protocol. In some embodiments, the processor 260 may be a generalpurpose processor (GPP), and in further embodiments, may have executableinstructions for performing processing of any security related protocol.

Although the hardware layer 206 of appliance 200 is illustrated withcertain elements in FIG. 2, the hardware portions or components ofappliance 200 may comprise any type and form of elements, hardware orsoftware, of a computing device, such as the computing device 100illustrated and discussed herein in conjunction with FIGS. 1E and 1F. Insome embodiments, the appliance 200 may comprise a server, gateway,router, switch, bridge or other type of computing or network device, andhave any hardware and/or software elements associated therewith.

The operating system of appliance 200 allocates, manages, or otherwisesegregates the available system memory into kernel space 204 and userspace 204. In example software architecture 200, the operating systemmay be any type and/or form of Unix operating system although theinvention is not so limited. As such, the appliance 200 can be runningany operating system such as any of the versions of the Microsoft®Windows operating systems, the different releases of the Unix and Linuxoperating systems, any version of the Mac OS® for Macintosh computers,any embedded operating system, any network operating system, anyreal-time operating system, any open source operating system, anyproprietary operating system, any operating systems for mobile computingdevices or network devices, or any other operating system capable ofrunning on the appliance 200 and performing the operations describedherein.

The kernel space 204 is reserved for running the kernel 230, includingany device drivers, kernel extensions or other kernel related software.As known to those skilled in the art, the kernel 230 is the core of theoperating system, and provides access, control, and management ofresources and hardware-related elements of the application 104. Inaccordance with an embodiment of the appliance 200, the kernel space 204also includes a number of network services or processes working inconjunction with a cache manager 232, sometimes also referred to as theintegrated cache, the benefits of which are described in detail furtherherein. Additionally, the embodiment of the kernel 230 will depend onthe embodiment of the operating system installed, configured, orotherwise used by the device 200.

In one embodiment, the device 200 comprises one network stack 267, suchas a TCP/IP based stack, for communicating with the client 102 and/orthe server 106. In one embodiment, the network stack 267 is used tocommunicate with a first network, such as network 108, and a secondnetwork 110. In some embodiments, the device 200 terminates a firsttransport layer connection, such as a TCP connection of a client 102,and establishes a second transport layer connection to a server 106 foruse by the client 102, e.g., the second transport layer connection isterminated at the appliance 200 and the server 106. The first and secondtransport layer connections may be established via a single networkstack 267. In other embodiments, the device 200 may comprise multiplenetwork stacks, for example 267 and 267′, and the first transport layerconnection may be established or terminated at one network stack 267,and the second transport layer connection on the second network stack267′. For example, one network stack may be for receiving andtransmitting network packet on a first network, and another networkstack for receiving and transmitting network packets on a secondnetwork. In one embodiment, the network stack 267 comprises a buffer 243for queuing one or more network packets for transmission by theappliance 200.

As shown in FIG. 2, the kernel space 204 includes the cache manager 232,a high-speed layer 2-7 integrated packet engine 240, an encryptionengine 234, a policy engine 236 and multi-protocol compression logic238. Running these components or processes 232, 240, 234, 236 and 238 inkernel space 204 or kernel mode instead of the user space 202 improvesthe performance of each of these components, alone and in combination.Kernel operation means that these components or processes 232, 240, 234,236 and 238 run in the core address space of the operating system of thedevice 200. For example, running the encryption engine 234 in kernelmode improves encryption performance by moving encryption and decryptionoperations to the kernel, thereby reducing the number of transitionsbetween the memory space or a kernel thread in kernel mode and thememory space or a thread in user mode. For example, data obtained inkernel mode may not need to be passed or copied to a process or threadrunning in user mode, such as from a kernel level data structure to auser level data structure. In another aspect, the number of contextswitches between kernel mode and user mode are also reduced.Additionally, synchronization of and communications between any of thecomponents or processes 232, 240, 235, 236 and 238 can be performed moreefficiently in the kernel space 204.

In some embodiments, any portion of the components 232, 240, 234, 236and 238 may run or operate in the kernel space 204, while other portionsof these components 232, 240, 234, 236 and 238 may run or operate inuser space 202. In one embodiment, the appliance 200 uses a kernel-leveldata structure providing access to any portion of one or more networkpackets, for example, a network packet comprising a request from aclient 102 or a response from a server 106. In some embodiments, thekernel-level data structure may be obtained by the packet engine 240 viaa transport layer driver interface or filter to the network stack 267.The kernel-level data structure may comprise any interface and/or dataaccessible via the kernel space 204 related to the network stack 267,network traffic or packets received or transmitted by the network stack267. In other embodiments, the kernel-level data structure may be usedby any of the components or processes 232, 240, 234, 236 and 238 toperform the desired operation of the component or process. In oneembodiment, a component 232, 240, 234, 236 and 238 is running in kernelmode 204 when using the kernel-level data structure, while in anotherembodiment, the component 232, 240, 234, 236 and 238 is running in usermode when using the kernel-level data structure. In some embodiments,the kernel-level data structure may be copied or passed to a secondkernel-level data structure, or any desired user-level data structure.

The cache manager 232 may comprise software, hardware or any combinationof software and hardware to provide cache access, control and managementof any type and form of content, such as objects or dynamicallygenerated objects served by the originating servers 106. The data,objects or content processed and stored by the cache manager 232 maycomprise data in any format, such as a markup language, or communicatedvia any protocol. In some embodiments, the cache manager 232 duplicatesoriginal data stored elsewhere or data previously computed, generated ortransmitted, in which the original data may require longer access timeto fetch, compute or otherwise obtain relative to reading a cache memoryelement. Once the data is stored in the cache memory element, future usecan be made by accessing the cached copy rather than refetching orrecomputing the original data, thereby reducing the access time. In someembodiments, the cache memory element may comprise a data object inmemory 264 of device 200. In other embodiments, the cache memory elementmay comprise memory having a faster access time than memory 264. Inanother embodiment, the cache memory element may comprise any type andform of storage element of the device 200, such as a portion of a harddisk. In some embodiments, the processing unit 262 may provide cachememory for use by the cache manager 232. In yet further embodiments, thecache manager 232 may use any portion and combination of memory,storage, or the processing unit for caching data, objects, and othercontent.

Furthermore, the cache manager 232 includes any logic, functions, rules,or operations to perform any embodiments of the techniques of theappliance 200 described herein. For example, the cache manager 232includes logic or functionality to invalidate objects based on theexpiration of an invalidation time period or upon receipt of aninvalidation command from a client 102 or server 106. In someembodiments, the cache manager 232 may operate as a program, service,process or task executing in the kernel space 204, and in otherembodiments, in the user space 202. In one embodiment, a first portionof the cache manager 232 executes in the user space 202 while a secondportion executes in the kernel space 204. In some embodiments, the cachemanager 232 can comprise any type of general purpose processor (GPP), orany other type of integrated circuit, such as a Field Programmable GateArray (FPGA), Programmable Logic Device (PLD), or Application SpecificIntegrated Circuit (ASIC).

The policy engine 236 may include, for example, an intelligentstatistical engine or other programmable application(s). In oneembodiment, the policy engine 236 provides a configuration mechanism toallow a user to identify, specify, define or configure a caching policy.Policy engine 236, in some embodiments, also has access to memory tosupport data structures such as lookup tables or hash tables to enableuser-selected caching policy decisions. In other embodiments, the policyengine 236 may comprise any logic, rules, functions or operations todetermine and provide access, control and management of objects, data orcontent being cached by the appliance 200 in addition to access, controland management of security, network traffic, network access, compressionor any other function or operation performed by the appliance 200.Further examples of specific caching policies are further describedherein.

The encryption engine 234 comprises any logic, business rules, functionsor operations for handling the processing of any security relatedprotocol, such as SSL or TLS, or any function related thereto. Forexample, the encryption engine 234 encrypts and decrypts networkpackets, or any portion thereof, communicated via the appliance 200. Theencryption engine 234 may also setup or establish SSL or TLS connectionson behalf of the client 102 a-102 n, server 106 a-106 n, or appliance200. As such, the encryption engine 234 provides offloading andacceleration of SSL processing. In one embodiment, the encryption engine234 uses a tunneling protocol to provide a virtual private networkbetween a client 102 a-102 n and a server 106 a-106 n. In someembodiments, the encryption engine 234 is in communication with theEncryption processor 260. In other embodiments, the encryption engine234 comprises executable instructions running on the Encryptionprocessor 260.

The multi-protocol compression engine 238 comprises any logic, businessrules, function or operations for compressing one or more protocols of anetwork packet, such as any of the protocols used by the network stack267 of the device 200. In one embodiment, multi-protocol compressionengine 238 compresses bi-directionally between clients 102 a-102 n andservers 106 a-106 n any TCP/IP based protocol, including MessagingApplication Programming Interface (MAPI) (email), File Transfer Protocol(FTP), HyperText Transfer Protocol (HTTP), Common Internet File System(CIFS) protocol (file transfer), Independent Computing Architecture(ICA) protocol, Remote Desktop Protocol (RDP), Wireless ApplicationProtocol (WAP), Mobile IP protocol, and Voice Over IP (VoIP) protocol.In other embodiments, multi-protocol compression engine 238 providescompression of Hypertext Markup Language (HTML) based protocols and insome embodiments, provides compression of any markup languages, such asthe Extensible Markup Language (XML). In one embodiment, themulti-protocol compression engine 238 provides compression of anyhigh-performance protocol, such as any protocol designed for appliance200 to appliance 200 communications. In another embodiment, themulti-protocol compression engine 238 compresses any payload of or anycommunication using a modified transport control protocol, such asTransaction TCP (T/TCP), TCP with selection acknowledgements (TCP-SACK),TCP with large windows (TCP-LW), a congestion prediction protocol suchas the TCP-Vegas protocol, and a TCP spoofing protocol.

As such, the multi-protocol compression engine 238 acceleratesperformance for users accessing applications via desktop clients, e.g.,Microsoft Outlook and non-Web thin clients, such as any client launchedby popular enterprise applications like Oracle, SAP and Siebel, and evenmobile clients, such as the Pocket PC. In some embodiments, themulti-protocol compression engine 238 by executing in the kernel mode204 and integrating with packet processing engine 240 accessing thenetwork stack 267 is able to compress any of the protocols carried bythe TCP/IP protocol, such as any application layer protocol.

High speed layer 2-7 integrated packet engine 240, also generallyreferred to as a packet processing engine or packet engine, isresponsible for managing the kernel-level processing of packets receivedand transmitted by appliance 200 via network ports 266. The high speedlayer 2-7 integrated packet engine 240 may comprise a buffer for queuingone or more network packets during processing, such as for receipt of anetwork packet or transmission of a network packet. Additionally, thehigh speed layer 2-7 integrated packet engine 240 is in communicationwith one or more network stacks 267 to send and receive network packetsvia network ports 266. The high speed layer 2-7 integrated packet engine240 works in conjunction with encryption engine 234, cache manager 232,policy engine 236 and multi-protocol compression logic 238. Inparticular, encryption engine 234 is configured to perform SSLprocessing of packets, policy engine 236 is configured to performfunctions related to traffic management such as request-level contentswitching and request-level cache redirection, and multi-protocolcompression logic 238 is configured to perform functions related tocompression and decompression of data.

The high speed layer 2-7 integrated packet engine 240 includes a packetprocessing timer 242. In one embodiment, the packet processing timer 242provides one or more time intervals to trigger the processing ofincoming, i.e., received, or outgoing, i.e., transmitted, networkpackets. In some embodiments, the high speed layer 2-7 integrated packetengine 240 processes network packets responsive to the timer 242. Thepacket processing timer 242 provides any type and form of signal to thepacket engine 240 to notify, trigger, or communicate a time relatedevent, interval or occurrence. In many embodiments, the packetprocessing timer 242 operates in the order of milliseconds, such as forexample 100 ms, 50 ms or 25 ms. For example, in some embodiments, thepacket processing timer 242 provides time intervals or otherwise causesa network packet to be processed by the high speed layer 2-7 integratedpacket engine 240 at a 10 ms time interval, while in other embodiments,at a 5 ms time interval, and still yet in further embodiments, as shortas a 3, 2, or 1 ms time interval. The high speed layer 2-7 integratedpacket engine 240 may be interfaced, integrated or in communication withthe encryption engine 234, cache manager 232, policy engine 236 andmulti-protocol compression engine 238 during operation. As such, any ofthe logic, functions, or operations of the encryption engine 234, cachemanager 232, policy engine 236 and multi-protocol compression logic 238may be performed responsive to the packet processing timer 242 and/orthe packet engine 240. Therefore, any of the logic, functions, oroperations of the encryption engine 234, cache manager 232, policyengine 236 and multi-protocol compression logic 238 may be performed atthe granularity of time intervals provided via the packet processingtimer 242, for example, at a time interval of less than or equal to 10ms. For example, in one embodiment, the cache manager 232 may performinvalidation of any cached objects responsive to the high speed layer2-7 integrated packet engine 240 and/or the packet processing timer 242.In another embodiment, the expiry or invalidation time of a cachedobject can be set to the same order of granularity as the time intervalof the packet processing timer 242, such as at every 10 ms.

In contrast to kernel space 204, user space 202 is the memory area orportion of the operating system used by user mode applications orprograms otherwise running in user mode. A user mode application may notaccess kernel space 204 directly and uses service calls in order toaccess kernel services. As shown in FIG. 2, user space 202 of appliance200 includes a graphical user interface (GUI) 210, a command lineinterface (CLI) 212, shell services 214, health monitoring program 216,and daemon services 218. GUI 210 and CLI 212 provide a means by which asystem administrator or other user can interact with and control theoperation of appliance 200, such as via the operating system of theappliance 200. The GUI 210 or CLI 212 can comprise code running in userspace 202 or kernel space 204. The GUI 210 may be any type and form ofgraphical user interface and may be presented via text, graphical orotherwise, by any type of program or application, such as a browser. TheCLI 212 may be any type and form of command line or text-basedinterface, such as a command line provided by the operating system. Forexample, the CLI 212 may comprise a shell, which is a tool to enableusers to interact with the operating system. In some embodiments, theCLI 212 may be provided via a bash, csh, tcsh, or ksh type shell. Theshell services 214 comprises the programs, services, tasks, processes orexecutable instructions to support interaction with the appliance 200 oroperating system by a user via the GUI 210 and/or CLI 212.

Health monitoring program 216 is used to monitor, check, report andensure that network systems are functioning properly and that users arereceiving requested content over a network. Health monitoring program216 comprises one or more programs, services, tasks, processes orexecutable instructions to provide logic, rules, functions or operationsfor monitoring any activity of the appliance 200. In some embodiments,the health monitoring program 216 intercepts and inspects any networktraffic passed via the appliance 200. In other embodiments, the healthmonitoring program 216 interfaces by any suitable means and/ormechanisms with one or more of the following: the encryption engine 234,cache manager 232, policy engine 236, multi-protocol compression logic238, packet engine 240, daemon services 218, and shell services 214. Assuch, the health monitoring program 216 may call any applicationprogramming interface (API) to determine a state, status, or health ofany portion of the appliance 200. For example, the health monitoringprogram 216 may ping or send a status inquiry on a periodic basis tocheck if a program, process, service or task is active and currentlyrunning In another example, the health monitoring program 216 may checkany status, error or history logs provided by any program, process,service or task to determine any condition, status or error with anyportion of the appliance 200.

Daemon services 218 are programs that run continuously or in thebackground and handle periodic service requests received by appliance200. In some embodiments, a daemon service may forward the requests toother programs or processes, such as another daemon service 218 asappropriate. As known to those skilled in the art, a daemon service 218may run unattended to perform continuous or periodic system widefunctions, such as network control, or to perform any desired task. Insome embodiments, one or more daemon services 218 run in the user space202, while in other embodiments, one or more daemon services 218 run inthe kernel space.

Referring now to FIG. 2B, another embodiment of the appliance 200 isdepicted. In brief overview, the appliance 200 provides one or more ofthe following services, functionality or operations: SSL VPNconnectivity 280, switching/load balancing 284, Domain Name Serviceresolution 286, acceleration 288 and an application firewall 290 forcommunications between one or more clients 102 and one or more servers106. Each of the servers 106 may provide one or more network relatedservices 270 a-270 n (referred to as services 270). For example, aserver 106 may provide an http service 270. The appliance 200 comprisesone or more virtual servers or virtual internet protocol servers,referred to as a vServer, VIP server, or just VIP 275 a-275 n (alsoreferred herein as vServer 275). The vServer 275 receives, intercepts orotherwise processes communications between a client 102 and a server 106in accordance with the configuration and operations of the appliance200.

The vServer 275 may comprise software, hardware or any combination ofsoftware and hardware. The vServer 275 may comprise any type and form ofprogram, service, task, process or executable instructions operating inuser mode 202, kernel mode 204 or any combination thereof in theappliance 200. The vServer 275 includes any logic, functions, rules, oroperations to perform any embodiments of the techniques describedherein, such as SSL VPN 280, switching/load balancing 284, Domain NameService resolution 286, acceleration 288 and an application firewall290. In some embodiments, the vServer 275 establishes a connection to aservice 270 of a server 106. The service 275 may comprise any program,application, process, task or set of executable instructions capable ofconnecting to and communicating to the appliance 200, client 102 orvServer 275. For example, the service 275 may comprise a web server,http server, ftp, email or database server. In some embodiments, theservice 270 is a daemon process or network driver for listening,receiving and/or sending communications for an application, such asemail, database or an enterprise application. In some embodiments, theservice 270 may communicate on a specific IP address, or IP address andport.

In some embodiments, the vServer 275 applies one or more policies of thepolicy engine 236 to network communications between the client 102 andserver 106. In one embodiment, the policies are associated with avServer 275. In another embodiment, the policies are based on a user, ora group of users. In yet another embodiment, a policy is global andapplies to one or more vServers 275 a-275 n, and any user or group ofusers communicating via the appliance 200. In some embodiments, thepolicies of the policy engine have conditions upon which the policy isapplied based on any content of the communication, such as internetprotocol address, port, protocol type, header or fields in a packet, orthe context of the communication, such as user, group of the user,vServer 275, transport layer connection, and/or identification orattributes of the client 102 or server 106.

In other embodiments, the appliance 200 communicates or interfaces withthe policy engine 236 to determine authentication and/or authorizationof a remote user or a remote client 102 to access the computingenvironment 15, application, and/or data file from a server 106. Inanother embodiment, the appliance 200 communicates or interfaces withthe policy engine 236 to determine authentication and/or authorizationof a remote user or a remote client 102 to have the application deliverysystem 190 deliver one or more of the computing environment 15,application, and/or data file. In yet another embodiment, the appliance200 establishes a VPN or SSL VPN connection based on the policy engine's236 authentication and/or authorization of a remote user or a remoteclient 102 In one embodiment, the appliance 200 controls the flow ofnetwork traffic and communication sessions based on policies of thepolicy engine 236. For example, the appliance 200 may control the accessto a computing environment 15, application or data file based on thepolicy engine 236.

In some embodiments, the vServer 275 establishes a transport layerconnection, such as a TCP or UDP connection with a client 102 via theclient agent 120. In one embodiment, the vServer 275 listens for andreceives communications from the client 102. In other embodiments, thevServer 275 establishes a transport layer connection, such as a TCP orUDP connection with a client server 106. In one embodiment, the vServer275 establishes the transport layer connection to an internet protocoladdress and port of a server 270 running on the server 106. In anotherembodiment, the vServer 275 associates a first transport layerconnection to a client 102 with a second transport layer connection tothe server 106. In some embodiments, a vServer 275 establishes a pool oftransport layer connections to a server 106 and multiplexes clientrequests via the pooled transport layer connections.

In some embodiments, the appliance 200 provides a SSL VPN connection 280between a client 102 and a server 106. For example, a client 102 on afirst network 102 requests to establish a connection to a server 106 ona second network 104′. In some embodiments, the second network 104′ isnot routable from the first network 104. In other embodiments, theclient 102 is on a public network 104 and the server 106 is on a privatenetwork 104′, such as a corporate network. In one embodiment, the clientagent 120 intercepts communications of the client 102 on the firstnetwork 104, encrypts the communications, and transmits thecommunications via a first transport layer connection to the appliance200. The appliance 200 associates the first transport layer connectionon the first network 104 to a second transport layer connection to theserver 106 on the second network 104. The appliance 200 receives theintercepted communication from the client agent 102, decrypts thecommunications, and transmits the communication to the server 106 on thesecond network 104 via the second transport layer connection. The secondtransport layer connection may be a pooled transport layer connection.As such, the appliance 200 provides an end-to-end secure transport layerconnection for the client 102 between the two networks 104, 104′.

In one embodiment, the appliance 200 hosts an intranet internet protocolor IntranetIP 282 address of the client 102 on the virtual privatenetwork 104. The client 102 has a local network identifier, such as aninternet protocol (IP) address and/or host name on the first network104. When connected to the second network 104′ via the appliance 200,the appliance 200 establishes, assigns or otherwise provides anIntranetIP address 282, which is a network identifier, such as IPaddress and/or host name, for the client 102 on the second network 104′.The appliance 200 listens for and receives on the second or privatenetwork 104′ for any communications directed towards the client 102using the client's established IntranetIP 282. In one embodiment, theappliance 200 acts as or on behalf of the client 102 on the secondprivate network 104. For example, in another embodiment, a vServer 275listens for and responds to communications to the IntranetIP 282 of theclient 102. In some embodiments, if a computing device 100 on the secondnetwork 104′ transmits a request, the appliance 200 processes therequest as if it were the client 102. For example, the appliance 200 mayrespond to a ping to the client's IntranetIP 282. In another example,the appliance may establish a connection, such as a TCP or UDPconnection, with computing device 100 on the second network 104requesting a connection with the client's IntranetIP 282.

In some embodiments, the appliance 200 provides one or more of thefollowing acceleration techniques 288 to communications between theclient 102 and server 106: 1) compression; 2) decompression; 3)Transmission Control Protocol pooling; 4) Transmission Control Protocolmultiplexing; 5) Transmission Control Protocol buffering; and 6)caching. In one embodiment, the appliance 200 relieves servers 106 ofmuch of the processing load caused by repeatedly opening and closingtransport layers connections to clients 102 by opening one or moretransport layer connections with each server 106 and maintaining theseconnections to allow repeated data accesses by clients via the Internet.This technique is referred to herein as “connection pooling”.

In some embodiments, in order to seamlessly splice communications from aclient 102 to a server 106 via a pooled transport layer connection, theappliance 200 translates or multiplexes communications by modifyingsequence number and acknowledgment numbers at the transport layerprotocol level. This is referred to as “connection multiplexing”. Insome embodiments, no application layer protocol interaction is required.For example, in the case of an in-bound packet (that is, a packetreceived from a client 102), the source network address of the packet ischanged to that of an output port of appliance 200, and the destinationnetwork address is changed to that of the intended server. In the caseof an outbound packet (that is, one received from a server 106), thesource network address is changed from that of the server 106 to that ofan output port of appliance 200 and the destination address is changedfrom that of appliance 200 to that of the requesting client 102. Thesequence numbers and acknowledgment numbers of the packet are alsotranslated to sequence numbers and acknowledgement numbers expected bythe client 102 on the appliance's 200 transport layer connection to theclient 102. In some embodiments, the packet checksum of the transportlayer protocol is recalculated to account for these translations.

In another embodiment, the appliance 200 provides switching orload-balancing functionality 284 for communications between the client102 and server 106. In some embodiments, the appliance 200 distributestraffic and directs client requests to a server 106 based on layer 4 orapplication-layer request data. In one embodiment, although the networklayer or layer 2 of the network packet identifies a destination server106, the appliance 200 determines the server 106 to distribute thenetwork packet by application information and data carried as payload ofthe transport layer packet. In one embodiment, the health monitoringprograms 216 of the appliance 200 monitor the health of servers todetermine the server 106 for which to distribute a client's request. Insome embodiments, if the appliance 200 detects a server 106 is notavailable or has a load over a predetermined threshold, the appliance200 can direct or distribute client requests to another server 106.

In some embodiments, the appliance 200 acts as a Domain Name Service(DNS) resolver or otherwise provides resolution of a DNS request fromclients 102. In some embodiments, the appliance intercepts a DNS requesttransmitted by the client 102. In one embodiment, the appliance 200responds to a client's DNS request with an IP address of or hosted bythe appliance 200. In this embodiment, the client 102 transmits networkcommunication for the domain name to the appliance 200. In anotherembodiment, the appliance 200 responds to a client's DNS request with anIP address of or hosted by a second appliance 200′. In some embodiments,the appliance 200 responds to a client's DNS request with an IP addressof a server 106 determined by the appliance 200.

In yet another embodiment, the appliance 200 provides applicationfirewall functionality 290 for communications between the client 102 andserver 106. In one embodiment, the policy engine 236 provides rules fordetecting and blocking illegitimate requests. In some embodiments, theapplication firewall 290 protects against denial of service (DoS)attacks. In other embodiments, the appliance inspects the content ofintercepted requests to identify and block application-based attacks. Insome embodiments, the rules/policy engine 236 comprises one or moreapplication firewall or security control policies for providingprotections against various classes and types of web or Internet basedvulnerabilities, such as one or more of the following: 1) bufferoverflow, 2) CGI-BIN parameter manipulation, 3) form/hidden fieldmanipulation, 4) forceful browsing, 5) cookie or session poisoning, 6)broken access control list (ACLs) or weak passwords, 7) cross-sitescripting (XSS), 8) command injection, 9) SQL injection, 10) errortriggering sensitive information leak, 11) insecure use of cryptography,12) server misconfiguration, 13) back doors and debug options, 14)website defacement, 15) platform or operating systems vulnerabilities,and 16) zero-day exploits. In an embodiment, the application firewall290 provides HTML form field protection in the form of inspecting oranalyzing the network communication for one or more of the following: 1)required fields are returned, 2) no added field allowed, 3) read-onlyand hidden field enforcement, 4) drop-down list and radio button fieldconformance, and 5) form-field max-length enforcement. In someembodiments, the application firewall 290 ensures cookies are notmodified. In other embodiments, the application firewall 290 protectsagainst forceful browsing by enforcing legal URLs.

In still yet other embodiments, the application firewall 290 protectsany confidential information contained in the network communication. Theapplication firewall 290 may inspect or analyze any networkcommunication in accordance with the rules or polices of the engine 236to identify any confidential information in any field of the networkpacket. In some embodiments, the application firewall 290 identifies inthe network communication one or more occurrences of a credit cardnumber, password, social security number, name, patient code, contactinformation, and age. The encoded portion of the network communicationmay comprise these occurrences or the confidential information. Based onthese occurrences, in one embodiment, the application firewall 290 maytake a policy action on the network communication, such as preventtransmission of the network communication. In another embodiment, theapplication firewall 290 may rewrite, remove or otherwise mask suchidentified occurrence or confidential information.

Still referring to FIG. 2B, the appliance 200 may include a performancemonitoring agent 197 as discussed above in conjunction with FIG. 1D. Inone embodiment, the appliance 200 receives the monitoring agent 197 fromthe monitoring service 198 or monitoring server 106 as depicted in FIG.1D. In some embodiments, the appliance 200 stores the monitoring agent197 in storage, such as disk, for delivery to any client or server incommunication with the appliance 200. For example, in one embodiment,the appliance 200 transmits the monitoring agent 197 to a client uponreceiving a request to establish a transport layer connection. In otherembodiments, the appliance 200 transmits the monitoring agent 197 uponestablishing the transport layer connection with the client 102. Inanother embodiment, the appliance 200 transmits the monitoring agent 197to the client upon intercepting or detecting a request for a web page.In yet another embodiment, the appliance 200 transmits the monitoringagent 197 to a client or a server in response to a request from themonitoring server 198. In one embodiment, the appliance 200 transmitsthe monitoring agent 197 to a second appliance 200′ or appliance 205.

In other embodiments, the appliance 200 executes the monitoring agent197. In one embodiment, the monitoring agent 197 measures and monitorsthe performance of any application, program, process, service, task orthread executing on the appliance 200. For example, the monitoring agent197 may monitor and measure performance and operation of vServers275A-275N. In another embodiment, the monitoring agent 197 measures andmonitors the performance of any transport layer connections of theappliance 200. In some embodiments, the monitoring agent 197 measuresand monitors the performance of any user sessions traversing theappliance 200. In one embodiment, the monitoring agent 197 measures andmonitors the performance of any virtual private network connectionsand/or sessions traversing the appliance 200, such an SSL VPN session.In still further embodiments, the monitoring agent 197 measures andmonitors the memory, CPU and disk usage and performance of the appliance200. In yet another embodiment, the monitoring agent 197 measures andmonitors the performance of any acceleration technique 288 performed bythe appliance 200, such as SSL offloading, connection pooling andmultiplexing, caching, and compression. In some embodiments, themonitoring agent 197 measures and monitors the performance of any loadbalancing and/or content switching 284 performed by the appliance 200.In other embodiments, the monitoring agent 197 measures and monitors theperformance of application firewall 290 protection and processingperformed by the appliance 200.

C. Client Agent

Referring now to FIG. 3, an embodiment of the client agent 120 isdepicted. The client 102 includes a client agent 120 for establishingand exchanging communications with the appliance 200 and/or server 106via a network 104. In brief overview, the client 102 operates oncomputing device 100 having an operating system with a kernel mode 302and a user mode 303, and a network stack 310 with one or more layers 310a-310 b. The client 102 may have installed and/or execute one or moreapplications. In some embodiments, one or more applications maycommunicate via the network stack 310 to a network 104. One of theapplications, such as a web browser, may also include a first program322. For example, the first program 322 may be used in some embodimentsto install and/or execute the client agent 120, or any portion thereof.The client agent 120 includes an interception mechanism, or interceptor350, for intercepting network communications from the network stack 310from the one or more applications.

The network stack 310 of the client 102 may comprise any type and formof software, or hardware, or any combinations thereof, for providingconnectivity to and communications with a network. In one embodiment,the network stack 310 comprises a software implementation for a networkprotocol suite. The network stack 310 may comprise one or more networklayers, such as any networks layers of the Open Systems Interconnection(OSI) communications model as those skilled in the art recognize andappreciate. As such, the network stack 310 may comprise any type andform of protocols for any of the following layers of the OSI model: 1)physical link layer, 2) data link layer, 3) network layer, 4) transportlayer, 5) session layer, 6) presentation layer, and 7) applicationlayer. In one embodiment, the network stack 310 may comprise a transportcontrol protocol (TCP) over the network layer protocol of the internetprotocol (IP), generally referred to as TCP/IP. In some embodiments, theTCP/IP protocol may be carried over the Ethernet protocol, which maycomprise any of the family of IEEE wide-area-network (WAN) orlocal-area-network (LAN) protocols, such as those protocols covered bythe IEEE 802.3. In some embodiments, the network stack 310 comprises anytype and form of a wireless protocol, such as IEEE 802.11 and/or mobileinternet protocol.

In view of a TCP/IP based network, any TCP/IP based protocol may beused, including Messaging Application Programming Interface (MAPI)(email), File Transfer Protocol (FTP), HyperText Transfer Protocol(HTTP), Common Internet File System (CIFS) protocol (file transfer),Independent Computing Architecture (ICA) protocol, Remote DesktopProtocol (RDP), Wireless Application Protocol (WAP), Mobile IP protocol,and Voice Over IP (VoIP) protocol. In another embodiment, the networkstack 310 comprises any type and form of transport control protocol,such as a modified transport control protocol, for example a TransactionTCP (T/TCP), TCP with selection acknowledgements (TCP-SACK), TCP withlarge windows (TCP-LW), a congestion prediction protocol such as theTCP-Vegas protocol, and a TCP spoofing protocol. In other embodiments,any type and form of user datagram protocol (UDP), such as UDP over IP,may be used by the network stack 310, such as for voice communicationsor real-time data communications.

Furthermore, the network stack 310 may include one or more networkdrivers supporting the one or more layers, such as a TCP driver or anetwork layer driver. The network drivers may be included as part of theoperating system of the computing device 100 or as part of any networkinterface cards or other network access components of the computingdevice 100. In some embodiments, any of the network drivers of thenetwork stack 310 may be customized, modified or adapted to provide acustom or modified portion of the network stack 310 in support of any ofthe techniques described herein. In other embodiments, the accelerationprogram 302 is designed and constructed to operate with or work inconjunction with the network stack 310 installed or otherwise providedby the operating system of the client 102.

The network stack 310 comprises any type and form of interfaces forreceiving, obtaining, providing or otherwise accessing any informationand data related to network communications of the client 102. In oneembodiment, an interface to the network stack 310 comprises anapplication programming interface (API). The interface may also compriseany function call, hooking or filtering mechanism, event or call backmechanism, or any type of interfacing technique. The network stack 310via the interface may receive or provide any type and form of datastructure, such as an object, related to functionality or operation ofthe network stack 310. For example, the data structure may compriseinformation and data related to a network packet or one or more networkpackets. In some embodiments, the data structure comprises a portion ofthe network packet processed at a protocol layer of the network stack310, such as a network packet of the transport layer. In someembodiments, the data structure 325 comprises a kernel-level datastructure, while in other embodiments, the data structure 325 comprisesa user-mode data structure. A kernel-level data structure may comprise adata structure obtained or related to a portion of the network stack 310operating in kernel-mode 302, or a network driver or other softwarerunning in kernel-mode 302, or any data structure obtained or receivedby a service, process, task, thread or other executable instructionsrunning or operating in kernel-mode of the operating system.

Additionally, some portions of the network stack 310 may execute oroperate in kernel-mode 302, for example, the data link or network layer,while other portions execute or operate in user-mode 303, such as anapplication layer of the network stack 310. For example, a first portion310 a of the network stack may provide user-mode access to the networkstack 310 to an application while a second portion 310 a of the networkstack 310 provides access to a network. In some embodiments, a firstportion 310 a of the network stack may comprise one or more upper layersof the network stack 310, such as any of layers 5-7. In otherembodiments, a second portion 310 b of the network stack 310 comprisesone or more lower layers, such as any of layers 1-4. Each of the firstportion 310 a and second portion 310 b of the network stack 310 maycomprise any portion of the network stack 310, at any one or morenetwork layers, in user-mode 203, kernel-mode, 202, or combinationsthereof, or at any portion of a network layer or interface point to anetwork layer or any portion of or interface point to the user-mode 203and kernel-mode 203.

The interceptor 350 may comprise software, hardware, or any combinationof software and hardware. In one embodiment, the interceptor 350intercept a network communication at any point in the network stack 310,and redirects or transmits the network communication to a destinationdesired, managed or controlled by the interceptor 350 or client agent120. For example, the interceptor 350 may intercept a networkcommunication of a network stack 310 of a first network and transmit thenetwork communication to the appliance 200 for transmission on a secondnetwork 104. In some embodiments, the interceptor 350 comprises any typeinterceptor 350 comprises a driver, such as a network driver constructedand designed to interface and work with the network stack 310. In someembodiments, the client agent 120 and/or interceptor 350 operates at oneor more layers of the network stack 310, such as at the transport layer.In one embodiment, the interceptor 350 comprises a filter driver,hooking mechanism, or any form and type of suitable network driverinterface that interfaces to the transport layer of the network stack,such as via the transport driver interface (TDI). In some embodiments,the interceptor 350 interfaces to a first protocol layer, such as thetransport layer and another protocol layer, such as any layer above thetransport protocol layer, for example, an application protocol layer. Inone embodiment, the interceptor 350 may comprise a driver complying withthe Network Driver Interface Specification (NDIS), or a NDIS driver. Inanother embodiment, the interceptor 350 may comprise a mini-filter or amini-port driver. In one embodiment, the interceptor 350, or portionthereof, operates in kernel-mode 202. In another embodiment, theinterceptor 350, or portion thereof, operates in user-mode 203. In someembodiments, a portion of the interceptor 350 operates in kernel-mode202 while another portion of the interceptor 350 operates in user-mode203. In other embodiments, the client agent 120 operates in user-mode203 but interfaces via the interceptor 350 to a kernel-mode driver,process, service, task or portion of the operating system, such as toobtain a kernel-level data structure 225. In further embodiments, theinterceptor 350 is a user-mode application or program, such asapplication.

In one embodiment, the interceptor 350 intercepts any transport layerconnection requests. In these embodiments, the interceptor 350 executetransport layer application programming interface (API) calls to set thedestination information, such as destination IP address and/or port to adesired location for the location. In this manner, the interceptor 350intercepts and redirects the transport layer connection to a IP addressand port controlled or managed by the interceptor 350 or client agent120. In one embodiment, the interceptor 350 sets the destinationinformation for the connection to a local IP address and port of theclient 102 on which the client agent 120 is listening. For example, theclient agent 120 may comprise a proxy service listening on a local IPaddress and port for redirected transport layer communications. In someembodiments, the client agent 120 then communicates the redirectedtransport layer communication to the appliance 200.

In some embodiments, the interceptor 350 intercepts a Domain NameService (DNS) request. In one embodiment, the client agent 120 and/orinterceptor 350 resolves the DNS request. In another embodiment, theinterceptor transmits the intercepted DNS request to the appliance 200for DNS resolution. In one embodiment, the appliance 200 resolves theDNS request and communicates the DNS response to the client agent 120.In some embodiments, the appliance 200 resolves the DNS request viaanother appliance 200′ or a DNS server 106.

In yet another embodiment, the client agent 120 may comprise two agents120 and 120′. In one embodiment, a first agent 120 may comprise aninterceptor 350 operating at the network layer of the network stack 310.In some embodiments, the first agent 120 intercepts network layerrequests such as Internet Control Message Protocol (ICMP) requests(e.g., ping and traceroute). In other embodiments, the second agent 120′may operate at the transport layer and intercept transport layercommunications. In some embodiments, the first agent 120 interceptscommunications at one layer of the network stack 210 and interfaces withor communicates the intercepted communication to the second agent 120′.

The client agent 120 and/or interceptor 350 may operate at or interfacewith a protocol layer in a manner transparent to any other protocollayer of the network stack 310. For example, in one embodiment, theinterceptor 350 operates or interfaces with the transport layer of thenetwork stack 310 transparently to any protocol layer below thetransport layer, such as the network layer, and any protocol layer abovethe transport layer, such as the session, presentation or applicationlayer protocols. This allows the other protocol layers of the networkstack 310 to operate as desired and without modification for using theinterceptor 350. As such, the client agent 120 and/or interceptor 350can interface with the transport layer to secure, optimize, accelerate,route or load-balance any communications provided via any protocolcarried by the transport layer, such as any application layer protocolover TCP/IP.

Furthermore, the client agent 120 and/or interceptor may operate at orinterface with the network stack 310 in a manner transparent to anyapplication, a user of the client 102, and any other computing device,such as a server, in communications with the client 102. The clientagent 120 and/or interceptor 350 may be installed and/or executed on theclient 102 in a manner without modification of an application. In someembodiments, the user of the client 102 or a computing device incommunications with the client 102 are not aware of the existence,execution or operation of the client agent 120 and/or interceptor 350.As such, in some embodiments, the client agent 120 and/or interceptor350 is installed, executed, and/or operated transparently to anapplication, user of the client 102, another computing device, such as aserver, or any of the protocol layers above and/or below the protocollayer interfaced to by the interceptor 350.

The client agent 120 includes an acceleration program 302, a streamingclient 306, a collection agent 304, and/or monitoring agent 197. In oneembodiment, the client agent 120 comprises an Independent ComputingArchitecture (ICA) client, or any portion thereof, developed by CitrixSystems, Inc. of Fort Lauderdale, Fla., and is also referred to as anICA client. In some embodiments, the client 120 comprises an applicationstreaming client 306 for streaming an application from a server 106 to aclient 102. In some embodiments, the client agent 120 comprises anacceleration program 302 for accelerating communications between client102 and server 106. In another embodiment, the client agent 120 includesa collection agent 304 for performing end-point detection/scanning andcollecting end-point information for the appliance 200 and/or server106.

In some embodiments, the acceleration program 302 comprises aclient-side acceleration program for performing one or more accelerationtechniques to accelerate, enhance or otherwise improve a client'scommunications with and/or access to a server 106, such as accessing anapplication provided by a server 106. The logic, functions, and/oroperations of the executable instructions of the acceleration program302 may perform one or more of the following acceleration techniques: 1)multi-protocol compression, 2) transport control protocol pooling, 3)transport control protocol multiplexing, 4) transport control protocolbuffering, and 5) caching via a cache manager. Additionally, theacceleration program 302 may perform encryption and/or decryption of anycommunications received and/or transmitted by the client 102. In someembodiments, the acceleration program 302 performs one or more of theacceleration techniques in an integrated manner or fashion.Additionally, the acceleration program 302 can perform compression onany of the protocols, or multiple-protocols, carried as a payload of anetwork packet of the transport layer protocol.

The streaming client 306 comprises an application, program, process,service, task or executable instructions for receiving and executing astreamed application from a server 106. A server 106 may stream one ormore application data files to the streaming client 306 for playing,executing or otherwise causing to be executed the application on theclient 102. In some embodiments, the server 106 transmits a set ofcompressed or packaged application data files to the streaming client306. In some embodiments, the plurality of application files arecompressed and stored on a file server within an archive file such as aCAB, ZIP, SIT, TAR, JAR or other archive. In one embodiment, the server106 decompresses, unpackages or unarchives the application files andtransmits the files to the client 102. In another embodiment, the client102 decompresses, unpackages or unarchives the application files. Thestreaming client 306 dynamically installs the application, or portionthereof, and executes the application. In one embodiment, the streamingclient 306 may be an executable program. In some embodiments, thestreaming client 306 may be able to launch another executable program.

The collection agent 304 comprises an application, program, process,service, task or executable instructions for identifying, obtainingand/or collecting information about the client 102. In some embodiments,the appliance 200 transmits the collection agent 304 to the client 102or client agent 120. The collection agent 304 may be configuredaccording to one or more policies of the policy engine 236 of theappliance. In other embodiments, the collection agent 304 transmitscollected information on the client 102 to the appliance 200. In oneembodiment, the policy engine 236 of the appliance 200 uses thecollected information to determine and provide access, authenticationand authorization control of the client's connection to a network 104.

In one embodiment, the collection agent 304 comprises an end-pointdetection and scanning mechanism, which identifies and determines one ormore attributes or characteristics of the client. For example, thecollection agent 304 may identify and determine any one or more of thefollowing client-side attributes: 1) the operating system an/or aversion of an operating system, 2) a service pack of the operatingsystem, 3) a running service, 4) a running process, and 5) a file. Thecollection agent 304 may also identify and determine the presence orversions of any one or more of the following on the client: 1) antivirussoftware, 2) personal firewall software, 3) anti-spam software, and 4)internet security software. The policy engine 236 may have one or morepolicies based on any one or more of the attributes or characteristicsof the client or client-side attributes.

In some embodiments, the client agent 120 includes a monitoring agent197 as discussed in conjunction with FIGS. 1D and 2B. The monitoringagent 197 may be any type and form of script, such as Visual Basic orJava script. In one embodiment, the monitoring agent 197 monitors andmeasures performance of any portion of the client agent 120. Forexample, in some embodiments, the monitoring agent 197 monitors andmeasures performance of the acceleration program 302. In anotherembodiment, the monitoring agent 197 monitors and measures performanceof the streaming client 306. In other embodiments, the monitoring agent197 monitors and measures performance of the collection agent 304. Instill another embodiment, the monitoring agent 197 monitors and measuresperformance of the interceptor 350. In some embodiments, the monitoringagent 197 monitors and measures any resource of the client 102, such asmemory, CPU and disk.

The monitoring agent 197 may monitor and measure performance of anyapplication of the client. In one embodiment, the monitoring agent 197monitors and measures performance of a browser on the client 102. Insome embodiments, the monitoring agent 197 monitors and measuresperformance of any application delivered via the client agent 120. Inother embodiments, the monitoring agent 197 measures and monitors enduser response times for an application, such as web-based or HTTPresponse times. The monitoring agent 197 may monitor and measureperformance of an ICA or RDP client. In another embodiment, themonitoring agent 197 measures and monitors metrics for a user session orapplication session. In some embodiments, monitoring agent 197 measuresand monitors an ICA or RDP session. In one embodiment, the monitoringagent 197 measures and monitors the performance of the appliance 200 inaccelerating delivery of an application and/or data to the client 102.

In some embodiments and still referring to FIG. 3, a first program 322may be used to install and/or execute the client agent 120, or portionthereof, such as the interceptor 350, automatically, silently,transparently, or otherwise. In one embodiment, the first program 322comprises a plugin component, such an ActiveX control or Java control orscript that is loaded into and executed by an application. For example,the first program comprises an ActiveX control loaded and run by a webbrowser application, such as in the memory space or context of theapplication. In another embodiment, the first program 322 comprises aset of executable instructions loaded into and run by the application,such as a browser. In one embodiment, the first program 322 comprises adesigned and constructed program to install the client agent 120. Insome embodiments, the first program 322 obtains, downloads, or receivesthe client agent 120 via the network from another computing device. Inanother embodiment, the first program 322 is an installer program or aplug and play manager for installing programs, such as network drivers,on the operating system of the client 102.

D. Systems and Methods for Providing Virtualized Application DeliveryController

Referring now to FIG. 4A, a block diagram depicts one embodiment of avirtualization environment 400. In brief overview, a computing device100 includes a hypervisor layer, a virtualization layer, and a hardwarelayer. The hypervisor layer includes a hypervisor 401 (also referred toas a virtualization manager) that allocates and manages access to anumber of physical resources in the hardware layer (e.g., theprocessor(s) 421, and disk(s) 428) by at least one virtual machineexecuting in the virtualization layer. The virtualization layer includesat least one operating system 410 and a plurality of virtual resourcesallocated to the at least one operating system 410. Virtual resourcesmay include, without limitation, a plurality of virtual processors 432a, 432 b, 432 c (generally 432), and virtual disks 442 a, 442 b, 442 c(generally 442), as well as virtual resources such as virtual memory andvirtual network interfaces. The plurality of virtual resources and theoperating system 410 may be referred to as a virtual machine 406. Avirtual machine 406 may include a control operating system 405 incommunication with the hypervisor 401 and used to execute applicationsfor managing and configuring other virtual machines on the computingdevice 100.

In greater detail, a hypervisor 401 may provide virtual resources to anoperating system in any manner which simulates the operating systemhaving access to a physical device. A hypervisor 401 may provide virtualresources to any number of guest operating systems 410 a, 410 b(generally 410). In some embodiments, a computing device 100 executesone or more types of hypervisors. In these embodiments, hypervisors maybe used to emulate virtual hardware, partition physical hardware,virtualize physical hardware, and execute virtual machines that provideaccess to computing environments. Hypervisors may include thosemanufactured by VMWare, Inc., of Palo Alto, Calif.; the XEN hypervisor,an open source product whose development is overseen by the open sourceXen.org community; HyperV, VirtualServer or virtual PC hypervisorsprovided by Microsoft, or others. In some embodiments, a computingdevice 100 executing a hypervisor that creates a virtual machineplatform on which guest operating systems may execute is referred to asa host server. In one of these embodiments, for example, the computingdevice 100 is a XEN SERVER provided by Citrix Systems, Inc., of FortLauderdale, Fla.

In some embodiments, a hypervisor 401 executes within an operatingsystem executing on a computing device. In one of these embodiments, acomputing device executing an operating system and a hypervisor 401 maybe said to have a host operating system (the operating system executingon the computing device), and a guest operating system (an operatingsystem executing within a computing resource partition provided by thehypervisor 401). In other embodiments, a hypervisor 401 interactsdirectly with hardware on a computing device, instead of executing on ahost operating system. In one of these embodiments, the hypervisor 401may be said to be executing on “bare metal,” referring to the hardwarecomprising the computing device.

In some embodiments, a hypervisor 401 may create a virtual machine 406a-c (generally 406) in which an operating system 410 executes. In one ofthese embodiments, for example, the hypervisor 401 loads a virtualmachine image to create a virtual machine 406. In another of theseembodiments, the hypervisor 401 executes an operating system 410 withinthe virtual machine 406. In still another of these embodiments, thevirtual machine 406 executes an operating system 410.

In some embodiments, the hypervisor 401 controls processor schedulingand memory partitioning for a virtual machine 406 executing on thecomputing device 100. In one of these embodiments, the hypervisor 401controls the execution of at least one virtual machine 406. In anotherof these embodiments, the hypervisor 401 presents at least one virtualmachine 406 with an abstraction of at least one hardware resourceprovided by the computing device 100. In other embodiments, thehypervisor 401 controls whether and how physical processor capabilitiesare presented to the virtual machine 406.

A control operating system 405 may execute at least one application formanaging and configuring the guest operating systems. In one embodiment,the control operating system 405 may execute an administrativeapplication, such as an application including a user interface providingadministrators with access to functionality for managing the executionof a virtual machine, including functionality for executing a virtualmachine, terminating an execution of a virtual machine, or identifying atype of physical resource for allocation to the virtual machine. Inanother embodiment, the hypervisor 401 executes the control operatingsystem 405 within a virtual machine 406 created by the hypervisor 401.In still another embodiment, the control operating system 405 executesin a virtual machine 406 that is authorized to directly access physicalresources on the computing device 100. In some embodiments, a controloperating system 405 a on a computing device 100 a may exchange datawith a control operating system 405 b on a computing device 100 b, viacommunications between a hypervisor 401 a and a hypervisor 401 b. Inthis way, one or more computing devices 100 may exchange data with oneor more of the other computing devices 100 regarding processors andother physical resources available in a pool of resources. In one ofthese embodiments, this functionality allows a hypervisor to manage apool of resources distributed across a plurality of physical computingdevices. In another of these embodiments, multiple hypervisors manageone or more of the guest operating systems executed on one of thecomputing devices 100.

In one embodiment, the control operating system 405 executes in avirtual machine 406 that is authorized to interact with at least oneguest operating system 410. In another embodiment, a guest operatingsystem 410 communicates with the control operating system 405 via thehypervisor 401 in order to request access to a disk or a network. Instill another embodiment, the guest operating system 410 and the controloperating system 405 may communicate via a communication channelestablished by the hypervisor 401, such as, for example, via a pluralityof shared memory pages made available by the hypervisor 401.

In some embodiments, the control operating system 405 includes a networkback-end driver for communicating directly with networking hardwareprovided by the computing device 100. In one of these embodiments, thenetwork back-end driver processes at least one virtual machine requestfrom at least one guest operating system 110. In other embodiments, thecontrol operating system 405 includes a block back-end driver forcommunicating with a storage element on the computing device 100. In oneof these embodiments, the block back-end driver reads and writes datafrom the storage element based upon at least one request received from aguest operating system 410.

In one embodiment, the control operating system 405 includes a toolsstack 404. In another embodiment, a tools stack 404 providesfunctionality for interacting with the hypervisor 401, communicatingwith other control operating systems 405 (for example, on a secondcomputing device 100 b), or managing virtual machines 406 b, 406 c onthe computing device 100. In another embodiment, the tools stack 404includes customized applications for providing improved managementfunctionality to an administrator of a virtual machine farm. In someembodiments, at least one of the tools stack 404 and the controloperating system 405 include a management API that provides an interfacefor remotely configuring and controlling virtual machines 406 running ona computing device 100. In other embodiments, the control operatingsystem 405 communicates with the hypervisor 401 through the tools stack404.

In one embodiment, the hypervisor 401 executes a guest operating system410 within a virtual machine 406 created by the hypervisor 401. Inanother embodiment, the guest operating system 410 provides a user ofthe computing device 100 with access to resources within a computingenvironment. In still another embodiment, a resource includes a program,an application, a document, a file, a plurality of applications, aplurality of files, an executable program file, a desktop environment, acomputing environment, or other resource made available to a user of thecomputing device 100. In yet another embodiment, the resource may bedelivered to the computing device 100 via a plurality of access methodsincluding, but not limited to, conventional installation directly on thecomputing device 100, delivery to the computing device 100 via a methodfor application streaming, delivery to the computing device 100 ofoutput data generated by an execution of the resource on a secondcomputing device 100′ and communicated to the computing device 100 via apresentation layer protocol, delivery to the computing device 100 ofoutput data generated by an execution of the resource via a virtualmachine executing on a second computing device 100′, or execution from aremovable storage device connected to the computing device 100, such asa USB device, or via a virtual machine executing on the computing device100 and generating output data. In some embodiments, the computingdevice 100 transmits output data generated by the execution of theresource to another computing device 100′.

In one embodiment, the guest operating system 410, in conjunction withthe virtual machine on which it executes, forms a fully-virtualizedvirtual machine which is not aware that it is a virtual machine; such amachine may be referred to as a “Domain U HVM (Hardware Virtual Machine)virtual machine”. In another embodiment, a fully-virtualized machineincludes software emulating a Basic Input/Output System (BIOS) in orderto execute an operating system within the fully-virtualized machine. Instill another embodiment, a fully-virtualized machine may include adriver that provides functionality by communicating with the hypervisor401. In such an embodiment, the driver may be aware that it executeswithin a virtualized environment. In another embodiment, the guestoperating system 410, in conjunction with the virtual machine on whichit executes, forms a paravirtualized virtual machine, which is awarethat it is a virtual machine; such a machine may be referred to as a“Domain U PV virtual machine”. In another embodiment, a paravirtualizedmachine includes additional drivers that a fully-virtualized machinedoes not include. In still another embodiment, the paravirtualizedmachine includes the network back-end driver and the block back-enddriver included in a control operating system 405, as described above.

Referring now to FIG. 4B, a block diagram depicts one embodiment of aplurality of networked computing devices in a system in which at leastone physical host executes a virtual machine. In brief overview, thesystem includes a management component 404 and a hypervisor 401. Thesystem includes a plurality of computing devices 100, a plurality ofvirtual machines 406, a plurality of hypervisors 401, a plurality ofmanagement components referred to variously as tools stacks 404 ormanagement components 404, and a physical resource 421, 428. Theplurality of physical machines 100 may each be provided as computingdevices 100, described above in connection with FIGS. 1E-1H and 4A.

In greater detail, a physical disk 428 is provided by a computing device100 and stores at least a portion of a virtual disk 442. In someembodiments, a virtual disk 442 is associated with a plurality ofphysical disks 428. In one of these embodiments, one or more computingdevices 100 may exchange data with one or more of the other computingdevices 100 regarding processors and other physical resources availablein a pool of resources, allowing a hypervisor to manage a pool ofresources distributed across a plurality of physical computing devices.In some embodiments, a computing device 100 on which a virtual machine406 executes is referred to as a physical host 100 or as a host machine100.

The hypervisor executes on a processor on the computing device 100. Thehypervisor allocates, to a virtual disk, an amount of access to thephysical disk. In one embodiment, the hypervisor 401 allocates an amountof space on the physical disk. In another embodiment, the hypervisor 401allocates a plurality of pages on the physical disk. In someembodiments, the hypervisor provisions the virtual disk 442 as part of aprocess of initializing and executing a virtual machine 450.

In one embodiment, the management component 404 a is referred to as apool management component 404 a. In another embodiment, a managementoperating system 405 a, which may be referred to as a control operatingsystem 405 a, includes the management component. In some embodiments,the management component is referred to as a tools stack. In one ofthese embodiments, the management component is the tools stack 404described above in connection with FIG. 4A. In other embodiments, themanagement component 404 provides a user interface for receiving, from auser such as an administrator, an identification of a virtual machine406 to provision and/or execute. In still other embodiments, themanagement component 404 provides a user interface for receiving, from auser such as an administrator, the request for migration of a virtualmachine 406 b from one physical machine 100 to another. In furtherembodiments, the management component 404 a identifies a computingdevice 100 b on which to execute a requested virtual machine 406 d andinstructs the hypervisor 401 b on the identified computing device 100 bto execute the identified virtual machine; such a management componentmay be referred to as a pool management component.

Referring now to FIG. 4C, embodiments of a virtual application deliverycontroller or virtual appliance 450 are depicted. In brief overview, anyof the functionality and/or embodiments of the appliance 200 (e.g., anapplication delivery controller) described above in connection withFIGS. 2A and 2B may be deployed in any embodiment of the virtualizedenvironment described above in connection with FIGS. 4A and 4B. Insteadof the functionality of the application delivery controller beingdeployed in the form of an appliance 200, such functionality may bedeployed in a virtualized environment 400 on any computing device 100,such as a client 102, server 106 or appliance 200.

Referring now to FIG. 4C, a diagram of an embodiment of a virtualappliance 450 operating on a hypervisor 401 of a server 106 is depicted.As with the appliance 200 of FIGS. 2A and 2B, the virtual appliance 450may provide functionality for availability, performance, offload andsecurity. For availability, the virtual appliance may perform loadbalancing between layers 4 and 7 of the network and may also performintelligent service health monitoring. For performance increases vianetwork traffic acceleration, the virtual appliance may perform cachingand compression. To offload processing of any servers, the virtualappliance may perform connection multiplexing and pooling and/or SSLprocessing. For security, the virtual appliance may perform any of theapplication firewall functionality and SSL VPN function of appliance200.

Any of the modules of the appliance 200 as described in connection withFIG. 2A may be packaged, combined, designed or constructed in a form ofthe virtualized appliance delivery controller 450 deployable as one ormore software modules or components executable in a virtualizedenvironment 300 or non-virtualized environment on any server, such as anoff the shelf server. For example, the virtual appliance may be providedin the form of an installation package to install on a computing device.With reference to FIG. 2A, any of the cache manager 232, policy engine236, compression 238, encryption engine 234, packet engine 240, GUI 210,CLI 212, shell services 214 and health monitoring programs 216 may bedesigned and constructed as a software component or module to run on anyoperating system of a computing device and/or of a virtualizedenvironment 300. Instead of using the encryption processor 260,processor 262, memory 264 and network stack 267 of the appliance 200,the virtualized appliance 400 may use any of these resources as providedby the virtualized environment 400 or as otherwise available on theserver 106.

Still referring to FIG. 4C, and in brief overview, any one or morevServers 275A-275N may be in operation or executed in a virtualizedenvironment 400 of any type of computing device 100, such as any server106. Any of the modules or functionality of the appliance 200 describedin connection with FIG. 2B may be designed and constructed to operate ineither a virtualized or non-virtualized environment of a server. Any ofthe vServer 275, SSL VPN 280, Intranet UP 282, Switching 284, DNS 286,acceleration 288, App FW 280 and monitoring agent may be packaged,combined, designed or constructed in a form of application deliverycontroller 450 deployable as one or more software modules or componentsexecutable on a device and/or virtualized environment 400.

In some embodiments, a server may execute multiple virtual machines 406a-406 n in the virtualization environment with each virtual machinerunning the same or different embodiments of the virtual applicationdelivery controller 450. In some embodiments, the server may execute oneor more virtual appliances 450 on one or more virtual machines on a coreof a multi-core processing system. In some embodiments, the server mayexecute one or more virtual appliances 450 on one or more virtualmachines on each processor of a multiple processor device.

E. Systems and Methods for Providing A Multi-Core Architecture

In accordance with Moore's Law, the number of transistors that may beplaced on an integrated circuit may double approximately every twoyears. However, CPU speed increases may reach plateaus, for example CPUspeed has been around 3.5-4 GHz range since 2005. In some cases, CPUmanufacturers may not rely on CPU speed increases to gain additionalperformance. Some CPU manufacturers may add additional cores to theirprocessors to provide additional performance. Products, such as those ofsoftware and networking vendors, that rely on CPUs for performance gainsmay improve their performance by leveraging these multi-core CPUs. Thesoftware designed and constructed for a single CPU may be redesignedand/or rewritten to take advantage of a multi-threaded, parallelarchitecture or otherwise a multi-core architecture. A multi-corearchitecture of the appliance 200, referred to as nCore or multi-coretechnology, allows the appliance in some embodiments to break the singlecore performance barrier and to leverage the power of multi-core CPUs.In the previous architecture described in connection with FIG. 2A, asingle network or packet engine is run. The multiple cores of the nCoretechnology and architecture allow multiple packet engines to runconcurrently and/or in parallel. With a packet engine running on eachcore, the appliance architecture leverages the processing capacity ofadditional cores. In some embodiments, this provides up to a 7× increasein performance and scalability.

Illustrated in FIG. 5A are some embodiments of work, task, load ornetwork traffic distribution across one or more processor coresaccording to a type of parallelism or parallel computing scheme, such asfunctional parallelism, data parallelism or flow-based data parallelism.In brief overview, FIG. 5A illustrates embodiments of a multi-coresystem such as an appliance 200′ with n-cores, a total of cores numbers1 through N. In one embodiment, work, load or network traffic can bedistributed among a first core 505A, a second core 505B, a third core505C, a fourth core 505D, a fifth core 505E, a sixth core 505F, aseventh core 505G, and so on such that distribution is across all or twoor more of the n cores 505N (hereinafter referred to collectively ascores 505.) There may be multiple VIPs 275 each running on a respectivecore of the plurality of cores. There may be multiple packet engines 240each running on a respective core of the plurality of cores. Any of theapproaches used may lead to different, varying or similar work load orperformance level 515 across any of the cores. For a functionalparallelism approach, each core may run a different function of thefunctionalities provided by the packet engine, a VIP 275 or appliance200. In a data parallelism approach, data may be paralleled ordistributed across the cores based on the Network Interface Card (NIC)or VIP 275 receiving the data. In another data parallelism approach,processing may be distributed across the cores by distributing dataflows to each core.

In further detail to FIG. 5A, in some embodiments, load, work or networktraffic can be distributed among cores 505 according to functionalparallelism 500. Functional parallelism may be based on each coreperforming one or more respective functions. In some embodiments, afirst core may perform a first function while a second core performs asecond function. In functional parallelism approach, the functions to beperformed by the multi-core system are divided and distributed to eachcore according to functionality. In some embodiments, functionalparallelism may be referred to as task parallelism and may be achievedwhen each processor or core executes a different process or function onthe same or different data. The core or processor may execute the sameor different code. In some cases, different execution threads or codemay communicate with one another as they work. Communication may takeplace to pass data from one thread to the next as part of a workflow.

In some embodiments, distributing work across the cores 505 according tofunctional parallelism 500, can comprise distributing network trafficaccording to a particular function such as network input/outputmanagement (NW I/O) 510A, secure sockets layer (SSL) encryption anddecryption 510B and transmission control protocol (TCP) functions 510C.This may lead to a work, performance or computing load 515 based on avolume or level of functionality being used. In some embodiments,distributing work across the cores 505 according to data parallelism540, can comprise distributing an amount of work 515 based ondistributing data associated with a particular hardware or softwarecomponent. In some embodiments, distributing work across the cores 505according to flow-based data parallelism 520, can comprise distributingdata based on a context or flow such that the amount of work 515A-N oneach core may be similar, substantially equal or relatively evenlydistributed.

In the case of the functional parallelism approach, each core may beconfigured to run one or more functionalities of the plurality offunctionalities provided by the packet engine or VIP of the appliance.For example, core 1 may perform network I/O processing for the appliance200′ while core 2 performs TCP connection management for the appliance.Likewise, core 3 may perform SSL offloading while core 4 may performlayer 7 or application layer processing and traffic management. Each ofthe cores may perform the same function or different functions. Each ofthe cores may perform more than one function. Any of the cores may runany of the functionality or portions thereof identified and/or describedin conjunction with FIGS. 2A and 2B. In this the approach, the workacross the cores may be divided by function in either a coarse-grainedor fine-grained manner. In some cases, as illustrated in FIG. 5A,division by function may lead to different cores running at differentlevels of performance or load 515.

In the case of the functional parallelism approach, each core may beconfigured to run one or more functionalities of the plurality offunctionalities provided by the packet engine of the appliance. Forexample, core 1 may perform network I/O processing for the appliance200′ while core 2 performs TCP connection management for the appliance.Likewise, core 3 may perform SSL offloading while core 4 may performlayer 7 or application layer processing and traffic management. Each ofthe cores may perform the same function or different functions. Each ofthe cores may perform more than one function. Any of the cores may runany of the functionality or portions thereof identified and/or describedin conjunction with FIGS. 2A and 2B. In this the approach, the workacross the cores may be divided by function in either a coarse-grainedor fine-grained manner. In some cases, as illustrated in FIG. 5Adivision by function may lead to different cores running at differentlevels of load or performance.

The functionality or tasks may be distributed in any arrangement andscheme. For example, FIG. 5B illustrates a first core, Core 1 505A,processing applications and processes associated with network I/Ofunctionality 510A. Network traffic associated with network I/O, in someembodiments, can be associated with a particular port number. Thus,outgoing and incoming packets having a port destination associated withNW I/O 510A will be directed towards Core 1 505A which is dedicated tohandling all network traffic associated with the NW I/O port. Similarly,Core 2 505B is dedicated to handling functionality associated with SSLprocessing and Core 4 505D may be dedicated handling all TCP levelprocessing and functionality.

While FIG. 5A illustrates functions such as network I/O, SSL and TCP,other functions can be assigned to cores. These other functions caninclude any one or more of the functions or operations described herein.For example, any of the functions described in conjunction with FIGS. 2Aand 2B may be distributed across the cores on a functionality basis. Insome cases, a first VIP 275A may run on a first core while a second VIP275B with a different configuration may run on a second core. In someembodiments, each core 505 can handle a particular functionality suchthat each core 505 can handle the processing associated with thatparticular function. For example, Core 2 505B may handle SSL offloadingwhile Core 4 505D may handle application layer processing and trafficmanagement.

In other embodiments, work, load or network traffic may be distributedamong cores 505 according to any type and form of data parallelism 540.In some embodiments, data parallelism may be achieved in a multi-coresystem by each core performing the same task or functionally ondifferent pieces of distributed data. In some embodiments, a singleexecution thread or code controls operations on all pieces of data. Inother embodiments, different threads or instructions control theoperation, but may execute the same code. In some embodiments, dataparallelism is achieved from the perspective of a packet engine,vServers (VIPs) 275A-C, network interface cards (NIC) 542D-E and/or anyother networking hardware or software included on or associated with anappliance 200. For example, each core may run the same packet engine orVIP code or configuration but operate on different sets of distributeddata. Each networking hardware or software construct can receivedifferent, varying or substantially the same amount of data, and as aresult may have varying, different or relatively the same amount of load515.

In the case of a data parallelism approach, the work may be divided upand distributed based on VIPs, NICs and/or data flows of the VIPs orNICs. In one of these approaches, the work of the multi-core system maybe divided or distributed among the VIPs by having each VIP work on adistributed set of data. For example, each core may be configured to runone or more VIPs. Network traffic may be distributed to the core foreach VIP handling that traffic. In another of these approaches, the workof the appliance may be divided or distributed among the cores based onwhich NIC receives the network traffic. For example, network traffic ofa first NIC may be distributed to a first core while network traffic ofa second NIC may be distributed to a second core. In some cases, a coremay process data from multiple NICs.

While FIG. 5A illustrates a single vServer associated with a single core505, as is the case for VIP1 275A, VIP2 275B and VIP3 275C. In someembodiments, a single vServer can be associated with one or more cores505. In contrast, one or more vServers can be associated with a singlecore 505. Associating a vServer with a core 505 may include that core505 to process all functions associated with that particular vServer. Insome embodiments, each core executes a VIP having the same code andconfiguration. In other embodiments, each core executes a VIP having thesame code but different configuration. In some embodiments, each coreexecutes a VIP having different code and the same or differentconfiguration.

Like vServers, NICs can also be associated with particular cores 505. Inmany embodiments, NICs can be connected to one or more cores 505 suchthat when a NIC receives or transmits data packets, a particular core505 handles the processing involved with receiving and transmitting thedata packets. In one embodiment, a single NIC can be associated with asingle core 505, as is the case with NIC1 542D and NIC2 542E. In otherembodiments, one or more NICs can be associated with a single core 505.In other embodiments, a single NIC can be associated with one or morecores 505. In these embodiments, load could be distributed amongst theone or more cores 505 such that each core 505 processes a substantiallysimilar amount of load. A core 505 associated with a NIC may process allfunctions and/or data associated with that particular NIC.

While distributing work across cores based on data of VIPs or NICs mayhave a level of independency, in some embodiments, this may lead tounbalanced use of cores as illustrated by the varying loads 515 of FIG.5A.

In some embodiments, load, work or network traffic can be distributedamong cores 505 based on any type and form of data flow. In another ofthese approaches, the work may be divided or distributed among coresbased on data flows. For example, network traffic between a client and aserver traversing the appliance may be distributed to and processed byone core of the plurality of cores. In some cases, the core initiallyestablishing the session or connection may be the core for which networktraffic for that session or connection is distributed. In someembodiments, the data flow is based on any unit or portion of networktraffic, such as a transaction, a request/response communication ortraffic originating from an application on a client. In this manner andin some embodiments, data flows between clients and servers traversingthe appliance 200′ may be distributed in a more balanced manner than theother approaches.

In flow-based data parallelism 520, distribution of data is related toany type of flow of data, such as request/response pairings,transactions, sessions, connections or application communications. Forexample, network traffic between a client and a server traversing theappliance may be distributed to and processed by one core of theplurality of cores. In some cases, the core initially establishing thesession or connection may be the core for which network traffic for thatsession or connection is distributed. The distribution of data flow maybe such that each core 505 carries a substantially equal or relativelyevenly distributed amount of load, data or network traffic.

In some embodiments, the data flow is based on any unit or portion ofnetwork traffic, such as a transaction, a request/response communicationor traffic originating from an application on a client. In this mannerand in some embodiments, data flows between clients and serverstraversing the appliance 200′ may be distributed in a more balancedmanner than the other approached. In one embodiment, data flow can bedistributed based on a transaction or a series of transactions. Thistransaction, in some embodiments, can be between a client and a serverand can be characterized by an IP address or other packet identifier.For example, Core 1 505A can be dedicated to transactions between aparticular client and a particular server, therefore the load 515A onCore 1 505A may be comprised of the network traffic associated with thetransactions between the particular client and server. Allocating thenetwork traffic to Core 1 505A can be accomplished by routing all datapackets originating from either the particular client or server to Core1 505A.

While work or load can be distributed to the cores based in part ontransactions, in other embodiments load or work can be allocated on aper packet basis. In these embodiments, the appliance 200 can interceptdata packets and allocate them to a core 505 having the least amount ofload. For example, the appliance 200 could allocate a first incomingdata packet to Core 1 505A because the load 515A on Core 1 is less thanthe load 515B-N on the rest of the cores 505B-N. Once the first datapacket is allocated to Core 1 505A, the amount of load 515A on Core 1505A is increased proportional to the amount of processing resourcesneeded to process the first data packet. When the appliance 200intercepts a second data packet, the appliance 200 will allocate theload to Core 4 505D because Core 4 505D has the second least amount ofload. Allocating data packets to the core with the least amount of loadcan, in some embodiments, ensure that the load 515A-N distributed toeach core 505 remains substantially equal.

In other embodiments, load can be allocated on a per unit basis where asection of network traffic is allocated to a particular core 505. Theabove-mentioned example illustrates load balancing on a per/packetbasis. In other embodiments, load can be allocated based on a number ofpackets such that every 10, 100 or 1000 packets are allocated to thecore 505 having the least amount of load. The number of packetsallocated to a core 505 can be a number determined by an application,user or administrator and can be any number greater than zero. In stillother embodiments, load can be allocated based on a time metric suchthat packets are distributed to a particular core 505 for apredetermined amount of time. In these embodiments, packets can bedistributed to a particular core 505 for five milliseconds or for anyperiod of time determined by a user, program, system, administrator orotherwise. After the predetermined time period elapses, data packets aretransmitted to a different core 505 for the predetermined period oftime.

Flow-based data parallelism methods for distributing work, load ornetwork traffic among the one or more cores 505 can comprise anycombination of the above-mentioned embodiments. These methods can becarried out by any part of the appliance 200, by an application or setof executable instructions executing on one of the cores 505, such asthe packet engine, or by any application, program or agent executing ona computing device in communication with the appliance 200.

The functional and data parallelism computing schemes illustrated inFIG. 5A can be combined in any manner to generate a hybrid parallelismor distributed processing scheme that encompasses function parallelism500, data parallelism 540, flow-based data parallelism 520 or anyportions thereof. In some cases, the multi-core system may use any typeand form of load balancing schemes to distribute load among the one ormore cores 505. The load balancing scheme may be used in any combinationwith any of the functional and data parallelism schemes or combinationsthereof.

Illustrated in FIG. 5B is an embodiment of a multi-core system 545,which may be any type and form of one or more systems, appliances,devices or components. This system 545, in some embodiments, can beincluded within an appliance 200 having one or more processing cores505A-N. The system 545 can further include one or more packet engines(PE) or packet processing engines (PPE) 548A-N communicating with amemory bus 556. The memory bus may be used to communicate with the oneor more processing cores 505A-N. Also included within the system 545 canbe one or more network interface cards (NIC) 552 and a flow distributor550 which can further communicate with the one or more processing cores505A-N. The flow distributor 550 can comprise a Receive Side Scaler(RSS) or Receive Side Scaling (RSS) module 560.

Further referring to FIG. 5B, and in more detail, in one embodiment thepacket engine(s) 548A-N can comprise any portion of the appliance 200described herein, such as any portion of the appliance described inFIGS. 2A and 2B. The packet engine(s) 548A-N can, in some embodiments,comprise any of the following elements: the packet engine 240, a networkstack 267; a cache manager 232; a policy engine 236; a compressionengine 238; an encryption engine 234; a GUI 210; a CLI 212; shellservices 214; monitoring programs 216; and any other software orhardware element able to receive data packets from one of either thememory bus 556 or the one of more cores 505A-N. In some embodiments, thepacket engine(s) 548A-N can comprise one or more vServers 275A-N, or anyportion thereof. In other embodiments, the packet engine(s) 548A-N canprovide any combination of the following functionalities: SSL VPN 280;Intranet UP 282; switching 284; DNS 286; packet acceleration 288; App FW280; monitoring such as the monitoring provided by a monitoring agent197; functionalities associated with functioning as a TCP stack; loadbalancing; SSL offloading and processing; content switching; policyevaluation; caching; compression; encoding; decompression; decoding;application firewall functionalities; XML processing and acceleration;and SSL VPN connectivity.

The packet engine(s) 548A-N can, in some embodiments, be associated witha particular server, user, client or network. When a packet engine 548becomes associated with a particular entity, that packet engine 548 canprocess data packets associated with that entity. For example, should apacket engine 548 be associated with a first user, that packet engine548 will process and operate on packets generated by the first user, orpackets having a destination address associated with the first user.Similarly, the packet engine 548 may choose not to be associated with aparticular entity such that the packet engine 548 can process andotherwise operate on any data packets not generated by that entity ordestined for that entity.

In some instances, the packet engine(s) 548A-N can be configured tocarry out any of the functional and/or data parallelism schemesillustrated in FIG. 5A. In these instances, the packet engine(s) 548A-Ncan distribute functions or data among the processing cores 505A-N sothat the distribution is according to the parallelism or distributionscheme. In some embodiments, a single packet engine(s) 548A-N carriesout a load balancing scheme, while in other embodiments one or morepacket engine(s) 548A-N carry out a load balancing scheme. Each core505A-N, in one embodiment, can be associated with a particular packetengine 548 such that load balancing can be carried out by the packetengine. Load balancing may in this embodiment, require that each packetengine 548A-N associated with a core 505 communicate with the otherpacket engines associated with cores so that the packet engines 548A-Ncan collectively determine where to distribute load. One embodiment ofthis process can include an arbiter that receives votes from each packetengine for load. The arbiter can distribute load to each packet engine548A-N based in part on the age of the engine's vote and in some cases apriority value associated with the current amount of load on an engine'sassociated core 505.

Any of the packet engines running on the cores may run in user mode,kernel or any combination thereof. In some embodiments, the packetengine operates as an application or program running is user orapplication space. In these embodiments, the packet engine may use anytype and form of interface to access any functionality provided by thekernel. In some embodiments, the packet engine operates in kernel modeor as part of the kernel. In some embodiments, a first portion of thepacket engine operates in user mode while a second portion of the packetengine operates in kernel mode. In some embodiments, a first packetengine on a first core executes in kernel mode while a second packetengine on a second core executes in user mode. In some embodiments, thepacket engine or any portions thereof operates on or in conjunction withthe NIC or any drivers thereof.

In some embodiments the memory bus 556 can be any type and form ofmemory or computer bus. While a single memory bus 556 is depicted inFIG. 5B, the system 545 can comprise any number of memory buses 556. Inone embodiment, each packet engine 548 can be associated with one ormore individual memory buses 556.

The NIC 552 can in some embodiments be any of the network interfacecards or mechanisms described herein. The NIC 552 can have any number ofports. The NIC can be designed and constructed to connect to any typeand form of network 104. While a single NIC 552 is illustrated, thesystem 545 can comprise any number of NICs 552. In some embodiments,each core 505A-N can be associated with one or more single NICs 552.Thus, each core 505 can be associated with a single NIC 552 dedicated toa particular core 505. The cores 505A-N can comprise any of theprocessors described herein. Further, the cores 505A-N can be configuredaccording to any of the core 505 configurations described herein. Stillfurther, the cores 505A-N can have any of the core 505 functionalitiesdescribed herein. While FIG. 5B illustrates seven cores 505A-G, anynumber of cores 505 can be included within the system 545. Inparticular, the system 545 can comprise “N” cores, where “N” is a wholenumber greater than zero.

A core may have or use memory that is allocated or assigned for use tothat core. The memory may be considered private or local memory of thatcore and only accessible by that core. A core may have or use memorythat is shared or assigned to multiple cores. The memory may beconsidered public or shared memory that is accessible by more than onecore. A core may use any combination of private and public memory. Withseparate address spaces for each core, some level of coordination iseliminated from the case of using the same address space. With aseparate address space, a core can perform work on information and datain the core's own address space without worrying about conflicts withother cores. Each packet engine may have a separate memory pool for TCPand/or SSL connections.

Further referring to FIG. 5B, any of the functionality and/orembodiments of the cores 505 described above in connection with FIG. 5Acan be deployed in any embodiment of the virtualized environmentdescribed above in connection with FIGS. 4A and 4B. Instead of thefunctionality of the cores 505 being deployed in the form of a physicalprocessor 505, such functionality may be deployed in a virtualizedenvironment 400 on any computing device 100, such as a client 102,server 106 or appliance 200. In other embodiments, instead of thefunctionality of the cores 505 being deployed in the form of anappliance or a single device, the functionality may be deployed acrossmultiple devices in any arrangement. For example, one device maycomprise two or more cores and another device may comprise two or morecores. For example, a multi-core system may include a cluster ofcomputing devices, a server farm or network of computing devices. Insome embodiments, instead of the functionality of the cores 505 beingdeployed in the form of cores, the functionality may be deployed on aplurality of processors, such as a plurality of single core processors.

In one embodiment, the cores 505 may be any type and form of processor.In some embodiments, a core can function substantially similar to anyprocessor or central processing unit described herein. In someembodiment, the cores 505 may comprise any portion of any processordescribed herein. While FIG. 5A illustrates seven cores, there can existany “N” number of cores within an appliance 200, where “N” is any wholenumber greater than one. In some embodiments, the cores 505 can beinstalled within a common appliance 200, while in other embodiments thecores 505 can be installed within one or more appliance(s) 200communicatively connected to one another. The cores 505 can in someembodiments comprise graphics processing software, while in otherembodiments the cores 505 provide general processing capabilities. Thecores 505 can be installed physically near each other and/or can becommunicatively connected to each other. The cores may be connected byany type and form of bus or subsystem physically and/or communicativelycoupled to the cores for transferring data between to, from and/orbetween the cores.

While each core 505 can comprise software for communicating with othercores, in some embodiments a core manager (not shown) can facilitatecommunication between each core 505. In some embodiments, the kernel mayprovide core management. The cores may interface or communicate witheach other using a variety of interface mechanisms. In some embodiments,core to core messaging may be used to communicate between cores, such asa first core sending a message or data to a second core via a bus orsubsystem connecting the cores. In some embodiments, cores maycommunicate via any type and form of shared memory interface. In oneembodiment, there may be one or more memory locations shared among allthe cores. In some embodiments, each core may have separate memorylocations shared with each other core. For example, a first core mayhave a first shared memory with a second core and a second share memorywith a third core. In some embodiments, cores may communicate via anytype of programming or API, such as function calls via the kernel. Insome embodiments, the operating system may recognize and supportmultiple core devices and provide interfaces and API for inter-corecommunications.

The flow distributor 550 can be any application, program, library,script, task, service, process or any type and form of executableinstructions executing on any type and form of hardware. In someembodiments, the flow distributor 550 may any design and construction ofcircuitry to perform any of the operations and functions describedherein. In some embodiments, the flow distributor distribute, forwards,routes, controls and/ors manage the distribution of data packets amongthe cores 505 and/or packet engine or VIPs running on the cores. Theflow distributor 550, in some embodiments, can be referred to as aninterface master. In one embodiment, the flow distributor 550 comprisesa set of executable instructions executing on a core or processor of theappliance 200. In another embodiment, the flow distributor 550 comprisesa set of executable instructions executing on a computing machine incommunication with the appliance 200. In some embodiments, the flowdistributor 550 comprises a set of executable instructions executing ona NIC, such as firmware. In still other embodiments, the flowdistributor 550 comprises any combination of software and hardware todistribute data packets among cores or processors. In one embodiment,the flow distributor 550 executes on at least one of the cores 505A-N,while in other embodiments a separate flow distributor 550 assigned toeach core 505A-N executes on an associated core 505A-N. The flowdistributor may use any type and form of statistical or probabilisticalgorithms or decision making to balance the flows across the cores. Thehardware of the appliance, such as a NIC, or the kernel may be designedand constructed to support sequential operations across the NICs and/orcores.

In embodiments where the system 545 comprises one or more flowdistributors 550, each flow distributor 550 can be associated with aprocessor 505 or a packet engine 548. The flow distributors 550 cancomprise an interface mechanism that allows each flow distributor 550 tocommunicate with the other flow distributors 550 executing within thesystem 545. In one instance, the one or more flow distributors 550 candetermine how to balance load by communicating with each other. Thisprocess can operate substantially similarly to the process describedabove for submitting votes to an arbiter which then determines whichflow distributor 550 should receive the load. In other embodiments, afirst flow distributor 550′ can identify the load on an associated coreand determine whether to forward a first data packet to the associatedcore based on any of the following criteria: the load on the associatedcore is above a predetermined threshold; the load on the associated coreis below a predetermined threshold; the load on the associated core isless than the load on the other cores; or any other metric that can beused to determine where to forward data packets based in part on theamount of load on a processor.

The flow distributor 550 can distribute network traffic among the cores505 according to a distribution, computing or load balancing scheme suchas those described herein. In one embodiment, the flow distributor candistribute network traffic according to any one of a functionalparallelism distribution scheme 550, a data parallelism loaddistribution scheme 540, a flow-based data parallelism distributionscheme 520, or any combination of these distribution scheme or any loadbalancing scheme for distributing load among multiple processors. Theflow distributor 550 can therefore act as a load distributor by takingin data packets and distributing them across the processors according toan operative load balancing or distribution scheme. In one embodiment,the flow distributor 550 can comprise one or more operations, functionsor logic to determine how to distribute packers, work or loadaccordingly. In still other embodiments, the flow distributor 550 cancomprise one or more sub operations, functions or logic that canidentify a source address and a destination address associated with adata packet, and distribute packets accordingly.

In some embodiments, the flow distributor 550 can comprise areceive-side scaling (RSS) network driver, module 560 or any type andform of executable instructions which distribute data packets among theone or more cores 505. The RSS module 560 can comprise any combinationof hardware and software, In some embodiments, the RSS module 560 worksin conjunction with the flow distributor 550 to distribute data packetsacross the cores 505A-N or among multiple processors in amulti-processor network. The RSS module 560 can execute within the NIC552 in some embodiments, and in other embodiments can execute on any oneof the cores 505.

In some embodiments, the RSS module 560 uses the MICROSOFTreceive-side-scaling (RSS) scheme. In one embodiment, RSS is a MicrosoftScalable Networking initiative technology that enables receiveprocessing to be balanced across multiple processors in the system whilemaintaining in-order delivery of the data. The RSS may use any type andform of hashing scheme to determine a core or processor for processing anetwork packet.

The RSS module 560 can apply any type and form hash function such as theToeplitz hash function. The hash function may be applied to the hashtype or any the sequence of values. The hash function may be a securehash of any security level or is otherwise cryptographically secure. Thehash function may use a hash key. The size of the key is dependent uponthe hash function. For the Toeplitz hash, the size may be 40 bytes forIPv6 and 16 bytes for IPv4.

The hash function may be designed and constructed based on any one ormore criteria or design goals. In some embodiments, a hash function maybe used that provides an even distribution of hash result for differenthash inputs and different hash types, including TCP/IPv4, TCP/IPv6,IPv4, and IPv6 headers. In some embodiments, a hash function may be usedthat provides a hash result that is evenly distributed when a smallnumber of buckets are present (for example, two or four). In someembodiments, hash function may be used that provides a hash result thatis randomly distributed when a large number of buckets were present (forexample, 64 buckets). In some embodiments, the hash function isdetermined based on a level of computational or resource usage. In someembodiments, the hash function is determined based on ease or difficultyof implementing the hash in hardware. In some embodiments, the hashfunction is determined based on the ease or difficulty of a maliciousremote host to send packets that would all hash to the same bucket.

The RSS may generate hashes from any type and form of input, such as asequence of values. This sequence of values can include any portion ofthe network packet, such as any header, field or payload of networkpacket, or portions thereof. In some embodiments, the input to the hashmay be referred to as a hash type and include any tuples of informationassociated with a network packet or data flow, such as any of thefollowing: a four tuple comprising at least two IP addresses and twoports; a four tuple comprising any four sets of values; a six tuple; atwo tuple; and/or any other sequence of numbers or values. The followingare example of hash types that may be used by RSS:

-   -   4-tuple of source TCP Port, source IP version 4 (IPv4) address,        destination TCP Port, and destination IPv4 address.    -   4-tuple of source TCP Port, source IP version 6 (IPv6) address,        destination TCP Port, and destination IPv6 address.    -   2-tuple of source IPv4 address, and destination IPv4 address.    -   2-tuple of source IPv6 address, and destination IPv6 address.    -   2-tuple of source IPv6 address, and destination IPv6 address,        including support for parsing IPv6 extension headers.

The hash result or any portion thereof may used to identify a core orentity, such as a packet engine or VIP, for distributing a networkpacket. In some embodiments, one or more hash bits or mask are appliedto the hash result. The hash bit or mask may be any number of bits orbytes. A NIC may support any number of bits, such as seven bits. Thenetwork stack may set the actual number of bits to be used duringinitialization. The number will be between 1 and 7, inclusive.

The hash result may be used to identify the core or entity via any typeand form of table, such as a bucket table or indirection table. In someembodiments, the number of hash-result bits are used to index into thetable. The range of the hash mask may effectively define the size of theindirection table. Any portion of the hash result or the hast resultitself may be used to index the indirection table. The values in thetable may identify any of the cores or processor, such as by a core orprocessor identifier. In some embodiments, all of the cores of themulti-core system are identified in the table. In other embodiments, aport of the cores of the multi-core system are identified in the table.The indirection table may comprise any number of buckets for example 2to 128 buckets that may be indexed by a hash mask. Each bucket maycomprise a range of index values that identify a core or processor. Insome embodiments, the flow controller and/or RSS module may rebalancethe network rebalance the network load by changing the indirectiontable.

In some embodiments, the multi-core system 575 does not include a RSSdriver or RSS module 560. In some of these embodiments, a softwaresteering module (not shown) or a software embodiment of the RSS modulewithin the system can operate in conjunction with or as part of the flowdistributor 550 to steer packets to cores 505 within the multi-coresystem 575.

The flow distributor 550, in some embodiments, executes within anymodule or program on the appliance 200, on any one of the cores 505 andon any one of the devices or components included within the multi-coresystem 575. In some embodiments, the flow distributor 550′ can executeon the first core 505A, while in other embodiments the flow distributor550″ can execute on the NIC 552. In still other embodiments, an instanceof the flow distributor 550′ can execute on each core 505 included inthe multi-core system 575. In this embodiment, each instance of the flowdistributor 550′ can communicate with other instances of the flowdistributor 550′ to forward packets back and forth across the cores 505.There exist situations where a response to a request packet may not beprocessed by the same core, i.e. the first core processes the requestwhile the second core processes the response. In these situations, theinstances of the flow distributor 550′ can intercept the packet andforward it to the desired or correct core 505, i.e. a flow distributorinstance 550′ can forward the response to the first core. Multipleinstances of the flow distributor 550′ can execute on any number ofcores 505 and any combination of cores 505.

The flow distributor may operate responsive to any one or more rules orpolicies. The rules may identify a core or packet processing engine toreceive a network packet, data or data flow. The rules may identify anytype and form of tuple information related to a network packet, such asa 4-tuple of source and destination IP address and source anddestination ports. Based on a received packet matching the tuplespecified by the rule, the flow distributor may forward the packet to acore or packet engine. In some embodiments, the packet is forwarded to acore via shared memory and/or core to core messaging.

Although FIG. 5B illustrates the flow distributor 550 as executingwithin the multi-core system 575, in some embodiments the flowdistributor 550 can execute on a computing device or appliance remotelylocated from the multi-core system 575. In such an embodiment, the flowdistributor 550 can communicate with the multi-core system 575 to takein data packets and distribute the packets across the one or more cores505. The flow distributor 550 can, in one embodiment, receive datapackets destined for the appliance 200, apply a distribution scheme tothe received data packets and distribute the data packets to the one ormore cores 505 of the multi-core system 575. In one embodiment, the flowdistributor 550 can be included in a router or other appliance such thatthe router can target particular cores 505 by altering meta dataassociated with each packet so that each packet is targeted towards asub-node of the multi-core system 575. In such an embodiment, CISCO'svn-tag mechanism can be used to alter or tag each packet with theappropriate meta data.

Illustrated in FIG. 5C is an embodiment of a multi-core system 575comprising one or more processing cores 505A-N. In brief overview, oneof the cores 505 can be designated as a control core 505A and can beused as a control plane 570 for the other cores 505. The other cores maybe secondary cores which operate in a data plane while the control coreprovides the control plane. The cores 505A-N may share a global cache580. While the control core provides a control plane, the other cores inthe multi-core system form or provide a data plane. These cores performdata processing functionality on network traffic while the controlprovides initialization, configuration and control of the multi-coresystem.

Further referring to FIG. 5C, and in more detail, the cores 505A-N aswell as the control core 505A can be any processor described herein.Furthermore, the cores 505A-N and the control core 505A can be anyprocessor able to function within the system 575 described in FIG. 5C.Still further, the cores 505A-N and the control core 505A can be anycore or group of cores described herein. The control core may be adifferent type of core or processor than the other cores. In someembodiments, the control may operate a different packet engine or have apacket engine configured differently than the packet engines of theother cores.

Any portion of the memory of each of the cores may be allocated to orused for a global cache that is shared by the cores. In brief overview,a predetermined percentage or predetermined amount of each of the memoryof each core may be used for the global cache. For example, 50% of eachmemory of each code may be dedicated or allocated to the shared globalcache. That is, in the illustrated embodiment, 2 GB of each coreexcluding the control plane core or core 1 may be used to form a 28 GBshared global cache. The configuration of the control plane such as viathe configuration services may determine the amount of memory used forthe shared global cache. In some embodiments, each core may provide adifferent amount of memory for use by the global cache. In otherembodiments, any one core may not provide any memory or use the globalcache. In some embodiments, any of the cores may also have a local cachein memory not allocated to the global shared memory. Each of the coresmay store any portion of network traffic to the global shared cache.Each of the cores may check the cache for any content to use in arequest or response. Any of the cores may obtain content from the globalshared cache to use in a data flow, request or response.

The global cache 580 can be any type and form of memory or storageelement, such as any memory or storage element described herein. In someembodiments, the cores 505 may have access to a predetermined amount ofmemory (i.e. 32 GB or any other memory amount commensurate with thesystem 575). The global cache 580 can be allocated from thatpredetermined amount of memory while the rest of the available memorycan be allocated among the cores 505. In other embodiments, each core505 can have a predetermined amount of memory. The global cache 580 cancomprise an amount of the memory allocated to each core 505. This memoryamount can be measured in bytes, or can be measured as a percentage ofthe memory allocated to each core 505. Thus, the global cache 580 cancomprise 1 GB of memory from the memory associated with each core 505,or can comprise 20 percent or one-half of the memory associated witheach core 505. In some embodiments, only a portion of the cores 505provide memory to the global cache 580, while in other embodiments theglobal cache 580 can comprise memory not allocated to the cores 505.

Each core 505 can use the global cache 580 to store network traffic orcache data. In some embodiments, the packet engines of the core use theglobal cache to cache and use data stored by the plurality of packetengines. For example, the cache manager of FIG. 2A and cachefunctionality of FIG. 2B may use the global cache to share data foracceleration. For example, each of the packet engines may storeresponses, such as HTML data, to the global cache. Any of the cachemanagers operating on a core may access the global cache to servercaches responses to client requests.

In some embodiments, the cores 505 can use the global cache 580 to storea port allocation table which can be used to determine data flow basedin part on ports. In other embodiments, the cores 505 can use the globalcache 580 to store an address lookup table or any other table or listthat can be used by the flow distributor to determine where to directincoming and outgoing data packets. The cores 505 can, in someembodiments read from and write to cache 580, while in other embodimentsthe cores 505 can only read from or write to cache 580. The cores mayuse the global cache to perform core to core communications.

The global cache 580 may be sectioned into individual memory sectionswhere each section can be dedicated to a particular core 505. In oneembodiment, the control core 505A can receive a greater amount ofavailable cache, while the other cores 505 can receiving varying amountsor access to the global cache 580.

In some embodiments, the system 575 can comprise a control core 505A.While FIG. 5C illustrates core 1 505A as the control core, the controlcore can be any core within the appliance 200 or multi-core system.Further, while only a single control core is depicted, the system 575can comprise one or more control cores each having a level of controlover the system. In some embodiments, one or more control cores can eachcontrol a particular aspect of the system 575. For example, one core cancontrol deciding which distribution scheme to use, while another corecan determine the size of the global cache 580.

The control plane of the multi-core system may be the designation andconfiguration of a core as the dedicated management core or as a mastercore. This control plane core may provide control, management andcoordination of operation and functionality the plurality of cores inthe multi-core system. This control plane core may provide control,management and coordination of allocation and use of memory of thesystem among the plurality of cores in the multi-core system, includinginitialization and configuration of the same. In some embodiments, thecontrol plane includes the flow distributor for controlling theassignment of data flows to cores and the distribution of networkpackets to cores based on data flows. In some embodiments, the controlplane core runs a packet engine and in other embodiments, the controlplane core is dedicated to management and control of the other cores ofthe system.

The control core 505A can exercise a level of control over the othercores 505 such as determining how much memory should be allocated toeach core 505 or determining which core 505 should be assigned to handlea particular function or hardware/software entity. The control core505A, in some embodiments, can exercise control over those cores 505within the control plan 570. Thus, there can exist processors outside ofthe control plane 570 which are not controlled by the control core 505A.Determining the boundaries of the control plane 570 can includemaintaining, by the control core 505A or agent executing within thesystem 575, a list of those cores 505 controlled by the control core505A. The control core 505A can control any of the following:initialization of a core; determining when a core is unavailable;re-distributing load to other cores 505 when one core fails; determiningwhich distribution scheme to implement; determining which core shouldreceive network traffic; determining how much cache should be allocatedto each core; determining whether to assign a particular function orelement to a particular core; determining whether to permit cores tocommunicate with one another; determining the size of the global cache580; and any other determination of a function, configuration oroperation of the cores within the system 575.

F. Systems and Methods for Aggregating Multi-Core Performance and TraceData

The systems and methods described in this section are directed towardsaggregating performance and trace data of a multi-core,multi-packet-engine appliance which manages network traffic. In variousembodiments, the appliance is disposed in a network intermediary to aplurality of clients and a plurality of servers which can providenetwork services or web content to the clients. The multi-core appliancecan manage connections between plural clients and plural servers as wellas manage web content exchanged between clients and servers.

In overview and referring now to FIG. 6A, an embodiment of a system 600for aggregating performance or trace data is depicted in block diagramform. The system 600 can be configured for operation on an appliance200. The appliance 200, as described elsewhere herein, can be adapted tooperate with the system 600 and provide information about networkperformance and trace data of the appliance. In various embodiments, theperformance and trace aggregating system 600 comprises packet engines548A-N, shared memory allocations 122B-N, an aggregator 610, and anagent interface 615. Each packet engine can manage network trafficbetween one or more clients 102 and one or more servers 106. Theaggregator 610 can communicate with the packet engines 548A-N via sharedmemory allocations 122B-N, as well as collect data through the sharedmemory allocations. The aggregator 610 can further communicate withagents 620A, 620B, which can request and receive information about theappliance's performance and trace data through the agent interface 615.The agent interface 615 can function as an intermediary between theagents 620 and the aggregator 610.

In various embodiments and in further detail, the packet engines 548A-Nexecute on a plurality of cores 505A-N of the appliance 200. Each packetengine can execute on a respective core and manage network traffic,e.g., exchange of web content, between one or more clients 102 and oneor more servers 106 in communication with the appliance 200. Aspects ofthe packet engines 548A-N and cores 505A-N are described elsewhereherein. Web content can include, without being limited to, HTTP or HTTPSrequests, HTTP or HTTPS responses, electronic mail, web pages, videodata, music or audio data, web forms, statistical data, plots, maps,books, advertisements, news or journal text, pictures, compiled datadescriptive of an item, event, weather, individual, group, organization,business, or geographical area. Each packet engine 548A-N can manageservices provided by servers 106. Web services can include, withoutbeing limited to, providing HTTP or HTTPs responses in reply to arequest, searching for specified information, carrying out calculations,compiling data, compiling statistics, providing for purchasing or saleof an item, executing a computer game, providing for electroniccommunication with another networked entity, etc. In variousembodiments, each packet engine 548A-N communicates with an allocation122B-N in memory 122.

In certain embodiments, each packet engine 548A-N is adapted to maintainone or more records 605PA-N, 605TA-N (generally 605) of certain aspectsof its operation, e.g., certain statistics or data about its operationas a virtual server (VIP 275A-N), data about servers to which eachpacket engine is currently maintaining active connections or has hadconnections to, data about a service managed by each packet engine, etc.In some embodiments, each packet engine maintains separate records forperformance data 650P and trace data 605T. In some embodiments, eachpacket engine maintains separate records for types of performance data,e.g., a record for VIP data, a record for subscribed service data. Insome embodiments, each packet engine maintains combined data records,e.g., one record for performance and trace data. In various embodiments,the records 605 provide information about performance statistics of eachpacket engine, and/or contain trace data captured by each packet engine.Each record 605A-N can comprise a data structure containing multiplerecords and types of data. Each record can be maintained with each corein memory 122, cache 140, in a data buffer, or any type of data storageelement accessible to each packet engine or its core.

Performance data 605P of the VIP 275 aspects of operation and/orperformance data for each packet engine can include, without beinglimited to, any of the following elements: the IP address and portconfiguration of the VIP, the state of the VIP, e.g., up, down, out ofservice, an indication of load balancing configuration of the VIP,number of hits on the VIP requesting web content, a measure of trafficpassed through the VIP, e.g., kbps, Mbps, Gbps, the persistenceconfiguration for the VIP, a measure of the number of times an errorpage was generated by the VIP, a measure of the volume of trafficpassing through the VIP, e.g., number of packets passing through theVIP, average size of a packet, number of active services that are boundto the VIP, the number of client connections to the VIP, the rate atwhich client connections are added or deleted from the VIP, the numberof server connections from the VIP in an “open” state, the number ofcurrent server connections from the VIP, and any combination thereof.

In some embodiments, the records 605 are maintained by each packetengine during operation, e.g., each packet engine can record theinformation periodically at selected time intervals. In some instances,each packet engine periodically overwrites data when recording theinformation, e.g., the data is written to the same space in a record atperiodic intervals, new data overwriting old data. In some instances,the data is written to memory in a manner to provide historical data,e.g., the data is recorded to a circular buffer having M sections. AfterM time intervals, older data is overwritten, however the buffer retainsa historical record of M time intervals at any instant. In variousembodiments, each packet engine can record the information stored in itsrespective record 605 or a portion thereof to a shared memory allocation122B-N or to non-shared memory. In some embodiments, the record isgenerated by the packet engine after it receives a request forinformation. A record generated after request can include informationabout all VIP operational aspects reportable by the packet engine, orcan include information about operational aspects specified in therequest.

Information about servers or service of a server for which the packetengine is managing service can include without being limited to, any ofthe following elements, which may be included in the performance data605P: the IP address and port configuration of the server, the state ofthe service provided by the server, e.g., up, down, out of service, thenumber of hits directed to the service, the number of hits directed tothe service due to configured server persistence, the number of activeconnections to the service, a measure of traffic to the service, e.g.,kbps, Mbps, Gbps, a bandwidth limit for the service, an average responsetime of the service, a measure of traffic volume to the service, e.g.,number of packets, average size of packets, a weight index used in loadbalancing for the service, a running hits count which can be used in around-robin load balancing algorithm, a number of connections to theservice, a rate at which connections to the service are added ordeleted, a maximum number of connections to the service at one time thathas been reached, a number of connections to the service in an “open”state, e.g., an open and active state, a number of connections to theservice residing in a reuse pool, e.g., open but not active, a number ofconnections to the service waiting in a serge queue, and any combinationthereof. In some embodiments, each record 605 of server or serviceinformation is maintained by each packet engine during operation, e.g.,each packet engine can record the information periodically at selectedtime intervals. In some instances, each packet engine periodicallyoverwrites data when recording the information, e.g., the data iswritten to the same space in the record at periodic intervals, new dataoverwriting old data. In some instances, the data is written to memoryin a manner to provide historical data, e.g., the data is recorded to acircular buffer having M sections. After M time intervals, older data isoverwritten, however the buffer retains a historical record of M timeintervals at any instant. In various embodiments, each packet engine canrecord the information from the records 605 to a shared memoryallocation 122B-N or to non-shared memory. In some embodiments, eachrecord 605 is generated by the packet engine after it receives a requestfor information. A record generated after a request can include allservice information reportable by the packet engine, or can includeservice information specified in the request.

In various embodiments, each packet engine 548A-N is adapted to capturetrace data. Trace data can identify network traffic or any portionthereof flowing through the packet engine during a selected timeinterval. Trace data can include any information related to the receipt,transmittal and processing of network packets and any hardware and/orsoftware related thereto, such as the packet engine, network stack andNIC. Trace data can include, without being limited to, any of theelements from the following list: requests for content, responses torequests for content, encrypted content, non-encrypted content, and anycombination thereof. Trace data can include identification of headers,fields and/or payload of a packet. Trace data can include identificationof a protocol of packet. Trace data can include identification of alayer of the network stack of a packet. Trace data can includeidentification of a NIC. Trace data include any temporal informationrelated to receipt, transmittal or processing of a network packet, suchany granularity of timestamp. Trace data include any informationidentifying operations, functions or actions of the packet engine inprocessing a network packet. Trace data may be represented in anyformat, arrangement, structure or representation.

In certain embodiments, each packet engine is further adapted to filterweb content passed by the packet engine in assembling trace data. As anexample, each packet engine can select for trace data web content inaccordance with a filtering criterion selected from the following list:source IP address, source port number, destination IP address,destination port number, service name, virtual server name, state ofservice, and any combination thereof. Combinations of these elements caninclude boolean combinations and compound expressions, e.g.,sourceip=105.2.1.2 AND servicename=map/boston. In various embodiments,trace data is generated after the packet engine receives a request fortrace data, the request specifying information desired in the trace anda time interval during which the trace is to be taken. If no informationis specified, all available trace data can be reported for a currentselected time interval. Trace data can be stored in separate tracerecords 605TA-N for each packet engine.

Memory allocations 122B-N can be defined in memory 122. Details ofmemory 122 are described elsewhere herein. Memory allocations 122B-N cancomprise locations and space in memory reserved for use by each packetengine and for use by the aggregator 610. The memory allocations 122B-Ncan be defined by each packet engine 548A-N, e.g., by using an IOCTL, asystem call, a subroutine, a function call, an API routine, a remoteprocedure call, etc., upon initialization of each packet engine, or canbe defined by the aggregator 610 upon initialization of the aggregator.The memory allocations can reside in kernel space or in user space. Insome embodiments, memory allocations are defined in kernel space andmapped to user space, or vice versa. The memory allocations can be localto the appliance 200, e.g., in cache or main memory of the appliance. Insome implementations, memory allocations are not local to the appliance,e.g., reserved on a storage device in communication with the appliance200 over a network 104.

In various embodiments, the memory allocations are shared between thepacket engines and the aggregator 610, e.g., both the aggregator and apacket engine 548 C can write and/or read data to and from a sharedallocation 122D. In some embodiments, each packet engine has its ownmemory allocation, e.g., engine 548A accesses only allocation 122B. Assuch, no two packet engines share a memory allocation, as depicted inFIG. 6A. In some embodiments, two or more packet engines share a memoryallocation. Sharing of memory allocations by packet engines can reducethe amount of memory reserved for performance and trace data.

In various embodiments, the performance and trace aggregating system 600further comprises an aggregator 610. The aggregator can comprisefirmware, software or any type and form of executable instructionsexecuting on a core of the multi-core appliance 200. In someembodiments, the aggregator 610 comprises executable instructions indistributed operation on plural cores of the appliance 200. Whenconfigured in distributed operation, communication between the cores bycore-to-core messaging, socket connections, or any other mode of datainterface can be used to coordinate operation of the aggregator 610. Insome embodiments, the aggregator 610 comprises executable instructionsexecuting on a processor dedicated for the aggregator. The dedicatedprocessor can be local to the appliance 200 or located apart from theappliance and in communication with the appliance over a network 104.

In some embodiments, the system 600 comprises two aggregators (notshown). One aggregator, e.g., a performance aggregator, can consolidateperformance data obtained from a plurality of packet engines 548A-B toproduce unified performance data 606A. One aggregator, e.g., a traceaggregator, can consolidate trace data obtained from a plurality ofpacket engines 548A-B to produce unified trace data 606B. In certainembodiments, the performance and trace aggregators operateindependently. For example, the aggregators may not communicate witheach other. In certain implementations, the performance and traceaggregators are in communication with each other. In some embodiments,the performance and trace aggregators are configured to operate on asame core of the multi-core appliance 200. In some embodiments, theperformance aggregator operates on a first core, and the traceaggregator operates on a second core of the multi-core appliance 200.

For embodiments where the appliance 200 has a performance aggregator anda separate trace aggregator, two sets of memory allocations 122B-N canbe established for each packet engine 548A-B. A first set of memoryallocations can store performance data from each packet engine, and thesecond set of memory allocations can store trace data from each packetengine. In such an embodiment, the performance aggregator shares accessto the first set of memory allocations with the packet engines, and thetrace aggregator shares access to the second set of memory allocations.

In certain embodiments, only one set of memory allocations 122B-N isestablished for an appliance 200 having a performance aggregator and atrace aggregator. In such an embodiment, the performance aggregator,trace aggregator, and packet engines can communicate with each otherthrough the shared memory allocations. Communications can be establishedby the setting of data flags, with or without accompanying commands, inthe shared memory allocation by each device. For example, theperformance aggregator can set a first flag to indicate a request forperformance data. Each packet engine can be configured to recognize thefirst flag and provide the requested data to its memory allocation, andset a second flag indicating the data is available. The trace aggregatorcan be configured to recognize the first flag and second flag and notset any flags while the request from the performance aggregator ispending. The performance aggregator can read data from the memoryallocations and set a third flag indicating that its request has beencompleted. The trace aggregator can recognize the third flag and set afourth flag in the shared memory indicating a request for trace data.Each packet engine can recognize the fourth flag, provide the requesteddata, and write a fifth flag to the shared memory indicating the datahas been written. The performance aggregator can recognize the fourthand fifth flags and not set any flags while the request from the traceaggregator is pending. The trace aggregator can read data from thememory allocations and set a sixth flag indicating that its request hasbeen completed. When the third or sixth flags are present in the sharedmemory allocations 122B-N, either the performance aggregator or traceaggregator may set a flag in the shared memory requesting data. In thismanner, the memory allocations 122B-N can be shared by the performanceaggregator and trace aggregator, as well as by the packet engines548A-N.

In various embodiments, the aggregator further comprises a buffer 122Afor storing data obtained from the packet engines 548A-N via the sharedmemory allocations 122B-N. The data obtained from the packet engines canbe stored directly into the buffer 122A, or processed before storinginto the buffer. Data stored in the buffer 122A can be exported, orprocessed and exported to agents 620 requesting data from the aggregator610. In certain embodiments, buffer 122A comprises a circular buffer,e.g., a circular page buffer, of sufficient size to store a selectedamount of operational data or web content obtained from each packetengine. In some cases, the size of the aggregator's buffer 122A issubstantially equivalent to the total size of all shared memoryallocations 122B-N. In some embodiments, the buffer 122A is mapped bythe aggregator upon its initialization, e.g., using IOCTL's, systemcalls, subroutines, function calls, API routines, remote procedurecalls, etc. In some embodiments, the buffer 122A is divided into twosections, one for performance data and one for trace data. In suchembodiments, additional space can be reserved for trace data.

In various embodiments, the aggregator 610 produces unified performancedata 606A or unified trace data 606B (hereafter sometimes generallyreferred to as “unified data” 606). The unified data 606 can be exportedto the interface agent 615 for forwarding to one or more agents 620requesting performance or trace data from the appliance 200. In variousembodiments, the unified data does not identify the plurality of cores505A-N and packet engines 548A-N of the appliance. As an example, anagent 620B receiving unified data 606 is unaware of the number of cores505 or packet processing engines 548 in operation on the appliance 200.The unified data 606 can comprise a data structure having multiplerecords and multiple data types. The unified data 606 can be stored inany data format on any memory device accessible to the aggregator. Insome embodiments, the unified data 606 is not stored by the aggregator,but exported to one or more agents 620. The unified data 606 can includeperformance statistics and trace data, described above, butrepresentative of the appliance 200 as though the appliance comprised asingle core. As an example, unified data 606 can include any aspect andtype of data about the appliance's operation as a virtual server (VIP275), data about servers to which the appliance is currently maintainingactive connections or has had connections to, data about a servicemanaged by the appliance, and/or trace data as described above inrelation to the packet engines. In various embodiments, the unifiedperformance or trace data 606 is representative of the appliance'snetwork performance or web content handled by the appliance as a whole.In some embodiments, the unified performance data is a collectiverepresentation of the local performance data from each of the packetengines and/or cores. In some embodiments, the unified performance datais a collective representation of the local trace data from each of thepacket engines and/or cores.

By way of an example, the aggregator 610 can produce the followingunified performance data 606A for a multi-core, multi-packet engineappliance 200:

VIP(141.128.58.149:80:UP:WEIGHTEDRR): Hits(38200495, 18/sec) Mbps(1.02)Pers(OFF) Err(0)

Pkt(186/sec, 610 bytes) actSvc(2) DefPol(NONE)

Conn: Clt(253, 1/sec, OE[252]) Svr(1)

SER1(141.128.49.40:80:UP) Hits(9443063, 4/sec, P[2602342, 0/sec]) ATr(5)Mbps(0.23) BW1mt(0 kbits)

RspTime(112.58 ms)

Other: Pkt(36/sec, 712 bytes) Wt(10000) RHits(31555)

Conn: CSvr(42, 0/sec) MCSvr(20) OE(16) RP(11) SQ(0)

SER2(141.128.49.39:80:UP) Hits(9731048, 4/sec, P[2929279, 0/sec]) ATr(9)Mbps(0.27) BW1mt(0 kbits)

RspTime (161.69 ms)

Other: Pkt(41/sec, 756 bytes) Wt(10000) RHits(31555)

Conn: CSvr(32, 0/sec) MCSvr(19) OE(13) RP(4) SQ(0)

In this example, the unified performance data comprises a record aboutvirtual service “VIP” provided by the appliance 200 and two recordsabout two servers “SER” providing services at the time the performancedata was requested. In the example, the VIP record contains thefollowing information or statistics: (IP address:port:state of theVIP:load balancing method configured for the VIP); (number of hitshandled by the VIP in a time interval, current rate of hits on the VIP);(rate of flow of traffic managed by the VIP in Mbps); (state ofpersistence configured for the VIP); (number of times an error page wasgenerated by the VIP in the time interval); (number of packets persecond passing through the VIP, average size of the packets flowingthrough the VIP); (number of active services that are bound to the VIP);(an indication of whether a default load balancing method is active);(the number of current client connections to the VIP, the current rateat which client connections are established or terminated); (the numberof server connections from the VIP in an established state); and (thenumber of servers actively providing service via the VIP). In theexample, each server record contains the following information orstatistics: (IP address:port:state of the service); (number of hitsdirected to the service in a time interval, current rate of hits,[number of hits directed to the service during the time interval due toconfigured server persistence, current rate of hits due to configuredserver persistence]), (number of active connections to the service);(rate of traffic flow passed to the service in Mbps); (a bandwidth limitdefined by the service); (an average response time of the service); (anaverage rate of traffic flow in terms of packets during the timeinterval, average size of the packets); (a weight index used in a loadbalancing algorithm); (a running hits counter used in round-robin loadbalancing); (the number of connections to the service, the current rateat which connections are established or terminated); (a maximum numberof connections to the service that has been reached); (a number ofconnections to the service in an established state); (a number ofconnections to the service residing in a reuse pool); (a number ofconnections to the service waiting in a serge queue). In this example,each of the values reported in a record can be obtained by totaling,averaging, or taking a weighted average of values from each packetengine 548A-N. For example, the number of client connections (253) tothe VIP can be determined by the aggregator 610 by summing clientconnections obtained from each of the packet engine's performance record605PA-N. In some embodiments, multiple occurrences of an aspect aresingly counted by the aggregator 610 in the reported value in theunified data. As such, a particular client having multiple connectionswith the VIP via different packet engines may only be counted as oneclient connection. Furthering the example, an average response time of aservice can be determined by the aggregator 610 by taking a weightedaverage of response times obtained from each packet engine's performancerecord 605PA-N. As such, each packet engine's recorded response time forthe service can be weighted by the number of hits directed by eachpacket engine to the service.

The aggregator 610 can also accumulate and provide unified trace data606B. In various embodiments, each packet engine 548A-N provides its ownrecord of trace data 605TA-N, which can be written to shared memoryallocations 122B-N. The aggregator 610 can read each packet engine'strace data and compile an aggregated or unified trace data structure606B. In some embodiments, the unified trace data 606B comprises aconcatenation of trace data from each packet processing engine 548A-N.The concatenation can be compiled according to one of several methods.The method used for concatenation can be specified during systemdevelopment time or specified in an agent request for unified tracedata.

In certain embodiments, unified trace data 606B comprises trace datafrom each packet engine concatenated by the core for the entire timeinterval of the trace. By way of an example in which a one-second timeinterval was specified for the trace and three packet engines 548A-Cwere actively passing web content during the interval, the unified tracedata comprises the web content passed by a first packet engine 548A,followed by the web content passed by a second packet engine 548B,followed by the web content passed by a third packet engine 548C, duringthe one-second interval. Although the concatenated trace data mightrepresent a three-second time frame, the unified trace data can bereported in “compressed” time, e.g., time scaled by the number of packetengines passing data at the same time.

In certain embodiments, unified trace data 606B comprises trace datafrom each packet engine concatenated by core for sub-intervals of theentire time interval of the trace. In the above example, theconcatenation method can be employed at each 100 ms, 10 ms, 1 ms, or anyother sub-interval of time. As such, the trace data recorded by eachpacket engine would be interleaved when compiling the unified trace data606B.

In some embodiments, unified trace data 606B comprises trace datasubstantially assembled according to streams of data exchanged between aparticular server and a particular client. In such embodiments, theaggregator 610 can group and concatenate packets of web contentaccording to source and destination IP addresses.

In certain aspects, the aggregator 610 communicates with each packetengine 548A-N using the shared memory allocations 122B-N. Communicationcan be carried out by setting and detecting the status of data flags inthe shared memory. As an example, the aggregator 610 can communicate arequest for performance data or trace data from a particular packetengine 548C by setting a data flag in the shared memory 122D. The packetengine 548C can monitor the memory 122D for the data flag, and upondetecting the flag write to the shared memory the requested data. Aftercompleting the writing, the packet engine can change the data flag orwrite a new data flag to the memory in a different location indicatingthe requested data has been written to the shared memory. The aggregator610 can also monitor the memory 122D for a change in status of the flag,or the addition of a new flag. Upon detecting a changed or new flag, theaggregator can read the data from the shared memory 122D.

It will be appreciated that a flag set by the aggregator can includeinformation identifying the requested data, e.g., performance data,certain elements of performance data, trace data, certain filteredelements of trace data. In some embodiments, the flag itself identifiesthe requested data or command to be carried out by each packet engine548A-N. For example, a first flag can identify a request for allperformance data, a second flag can identify a request for a firstsubset of elements of performance data, e.g., elements of virtualservice, a third flag can identify a request for a second subset ofelements of performance data, e.g., elements of a first service or afirst server, a fourth flag can identify a request for trace data, etc.In such embodiments, each packet engine 548A-N can be configured torecognize the one or more flags and identify the requested elements fromthe flag itself. In some embodiments, the flag is accompanied by datawritten in the shared memory by the aggregator 610, wherein theaccompanying data identifies the requested data or command to be carriedout by each packet engine. It will be appreciated that the aggregator610 can set the same flags in all memory allocations 122B-N shared withthe packet engines 548A-N, or can set different flags in the memoryallocations.

When shared memory is further shared by packet engines, e.g., packetengines 548A and 548B share allocation 122B, communication via flags andtime multiplexing can be employed to manage data written to and readfrom the shared memory. As an example, the aggregator 610 can requestsequentially data from the two packet engines 548A and 548B in thisexample. A first flag identifying a first packet engine 548A and a datarequest can be written by the aggregator to the shared memory 122B.Packet engine 548A monitoring the memory can detect the flag, write therequested data to the memory 122B, and alter the flag or add a new flagto indicate it has written the data to the memory, while packet engine548B ignores the flag since the flag does not identify engine 548B.Aggregator 610 can read the data provided by the first packet engine548A from the memory 122B, and write a second flag identifying thesecond packet engine 548B and data requested. The second flag canreplace the first flag or altered flag. Packet engine 548B can detectthe flag, write the requested data to the memory 122B, and alter theflag or add a new flag to indicate it has written the data to thememory, while packet engine 548A ignores the flag. Aggregator 610 canthen read the data provided by the second packet engine 548B.

In various embodiments, aggregator 610 is adapted to communicate withagents 620. The communication with agents 620 can be via an agentinterface 615. The agent interface can comprise software, firmware orany type and form of executable instructions executing on a core of theappliance. In some embodiments, the agent interface 615 comprises a setof instructions which are part of the aggregator 610. In someembodiments, the agent interface 615 comprises a set of instructionsoperating separately from the aggregator 610. In some instances, theagent interface is in operation on the same core as that for theaggregator, and in some cases the agent interface 615 is in operation ona different core from that on which the aggregator 610 operates. Invarious embodiments, the agent interface 615 communicates with theaggregator 610 via socket connections.

In certain embodiments, the agent interface 615 comprises two IP ports,e.g., port 3333 and port 5555, and software associated with establishingand maintaining socket connections on these ports. One port can be usedfor receiving requests from and transmitting data to one or more agents620, such as the data relating to performance statistics. One port canbe used for receiving requests from and transmitting data to one or moreagents, such as the data relating to trace data. In certain embodiments,the aggregator 610 is configured to listen for socket connections onports of the agent interface 615. In some embodiments, the agentinterface comprises one or more data files. As an example, data requestscan be written to a “data request” file by an agent 620A and read fromthe file by the aggregator 610. The aggregator can write the requesteddata to a “data return” file, which can be read by the agent. In someembodiments, the agent interface 615 comprises software which translatesrequests received from one or more applications into a formatrecognizable by the aggregator 610.

An agent 620A, 620B (generally 620) can comprise any entity requestingperformance or trace data from the appliance 200. An agent can be asystem operator or administrator entering commands in a command lineinterface (CLI) in communication with the appliance. An agent cancomprise a graphical user interface, dashboard, proprietary software, orpublicly available software, e.g., TCPDUMP, Wireshark, NETSVC, SNMP,etc., configured to communicate with the appliance 200. In someembodiments, an agent comprises another networked device, e.g., a server106, a client 102, or another appliance 200′, which periodicallyinterrogates the appliance 200 for performance or trace data. In certainembodiments, an agent is a connection, module or agent of a client forinterfacing with and/or gathering information from the aggregator.

Referring now to FIG. 6B, an embodiment of method 650 for use with theperformance and trace aggregating system 600 is depicted. In variousembodiments, the method 650 comprises collecting or capturing 652 databy each packet engine, storing 664 data to a buffer by the aggregator,consolidating 666 the data by the aggregator, receiving 668 a requestfor data by the aggregator, and transmitting 670 the consolidated databy the aggregator in response to the request. This and other steps-baseddepictions in this disclosure are not intended to portray a specificsequence of the steps, and certain steps can be performed before orafter other steps. The method can comprise a subset of the stepsdepicted, and in some embodiments include additional steps as describedbelow.

In certain embodiments, the step of collecting 652 comprises collectingby each packet engine performance data identifying statistics of aservice provided by a server for which each packet engine managesnetwork traffic. In some embodiments, the performance data identifiesstatistics of a server or service only associated with a current oractive connection between each packet engine and the server providingthe service. In some embodiments, the performance data identifiesstatistics of a server or service associated with a past connection to aserver. In certain embodiments, the collected performance dataidentifies statistics of virtual service provided by each packet engine.The performance data can include any element of information aboutvirtual service of each packet engine as described above, e.g., the IPaddress and port configuration of the VIP, the state of the VIP, etc.The performance data can include, alternatively or in addition to theVIP data, any element of information about the server or service of theserver as describe above, e.g., the IP address and port configuration ofthe server, the state of the service provided by the server, etc. Insome embodiments, the step of capturing 652 comprises capturing, by eachpacket engine, trace information for network traffic received ortransmitted by each packet engine. Trace data can include, without beinglimited to, any element from the following list: requests for webcontent, responses to requests for web content, encrypted web content,non-encrypted web content, and any combination thereof as describedabove. In some embodiments, the collecting 652 of performance data isdone periodically, e.g., every 10 seconds, every 7 seconds, every 3seconds, every 1 second, by each packet engine. In various embodiments,the step of collecting 652 further comprises determining, by each packetengine 548A-N, performance statistics and recording the statistics toperformance records 605PA-N. In various embodiments, the step ofcapturing 652 comprises recording, by each packet engine, trace data totrace records 605TA-N. In some embodiments, collecting 652 ofperformance data is done in response to a request for performance dataindicated by the aggregator 610. In certain embodiments, the capturing652 of trace data is done in response to a request for trace dataindicated by the aggregator 610.

Further aspects of an embodiment of the step of collecting or capturing652 are depicted in FIG. 6C. In certain embodiments, the step ofcollecting or capturing 652 comprises sending or storing 654 a commandand setting 655 a flag by the aggregator in each shared memoryallocation 122B-N for each of the plurality of packet engines. In someembodiments, the data flag comprises an indicator and a command. Theindicator can identify a status of the request, e.g., data requested, nodata requested, data requested at a specified time, data requested for aspecified time interval, data requested for a particular packet engine,etc. The command can comprise details about the elements of datarequested as well as specific types of actions, e.g., provide virtualservice data, dump all data immediately, terminate data collection,terminate data capturing, begin data capturing, filter data inaccordance with specified filtering criteria. In various embodiments,the step of collecting or capturing 652 further comprises changing, byeach packet engine, the data flag in shared memory allocations 122B-Nwhen each packet engine completes the step of collecting or capturing652.

The step of collecting or capturing 652 can further comprise detecting,by each packet engine, the data flag set by the aggregator 610 in memoryshared between the packet engine and the aggregator. Each packet engine548A-N can monitor the shared memory for the data flag. Each packetengine can further interpret any data, e.g., a command set by theaggregator 610, included with the flag and identifying certain aspectsof data requested, e.g., performance data, certain elements ofperformance data, trace data, filtered elements of trace data, timeintervals associated with the data. Data included with the flag can alsoinclude IOCTLs, objects, data structures, function calls, procedurecalls, routines, macros, and the like.

The step of collecting 652 can comprise executing, by each packetengine, diagnostic routines to compile performance statistics for eachpacket engine. The diagnostic routines can identify performance data orcertain elements of performance data as requested by the aggregator 610.In some embodiments, the routines can comprise maintaining counterswhich determine any of the following types of values, total number,maximum number, minimum number, average number, frequency, etc. The stepof collecting 652 can comprise collecting data for current activeconnections between active clients and servers actively providingservice. In some embodiments, the step of collecting 652 can comprisecollecting data historical data of performance statistics stored in anarchive accessible to the packet engine. The step of capturing 652 canfurther comprise executing routines by the packet engine to recordduring a selected time interval network traffic passed by the packetengine, e.g., record trace data during a specified time interval. Insome embodiments, the capturing further comprises filtering the captureddata. The filtering can comprise recording, by each packet engine, onlynetwork traffic which meets a filter criterion, e.g., from a particularsource IP address, during a particular time interval, to a particulardestination IP address, etc.

In various embodiments, the step of collecting or capturing 652 furthercomprises collecting or capturing data by each packet engine for aselected time interval. The selected time interval can be identified bythe aggregator 610, and established with the data flag and/or commandset by the aggregator in shared memory 122B-N. In certain embodiments, adefault time interval is used for instances when no time interval isspecified by the aggregator. In various embodiments, the step ofcollecting or capturing 652 further comprises writing, by each packetengine, performance data or trace data to the shared memory allocations122B-N. The performance data can be written, by each packet engine, tothe shared memory allocations 122B-N from each packet engine'sperformance record 605PA-N. The trace data can be written, by eachpacket engine, to the shared memory allocations 122B-N from each packetengine's trace record 605TA-N.

Referring again to FIG. 6C, the step of collecting or capturing 652 canfurther comprise monitoring, by the aggregator, the status of the dataflags set in each shared memory allocation 122B-N to determine 656Awhether each flag's status has changed. If it is determined that aflag's status has changed, the aggregator 610 can read 657 performancedata or trace data from the shared memory allocation indicated by thechanged flag status. If it is determined that a flag's status has notchanged, the aggregator 610 can determine 656B whether a packet engineis slow in providing the requested data, e.g., the packet engine has notprovided the requested data within a specified time window. If it isdetermined that the packet engine is not slow, the aggregator canexecute 658 another task and return to checking 656A the flag status ata later time. If it is determined 656B that the packet engine is slow inproviding the data, the aggregator 610 can issue a command which forces659 the packet engine to dump its performance data or trace data. Theaggregator 610 can then read 657 the dumped data. In cases where aforced dump is executed by a packet engine and the packet engine has notcomplete all of its data acquisition, any remaining data values to beacquired or any remaining data trace to be acquired can be representedas zero values when the packet engine writes the acquired data to theshared memory allocation.

The step of storing data 664 can comprise storing to a buffer 122A bythe aggregator 610 performance data or trace data from each packetengine. In some embodiments, the step of storing 664 comprises storing,by the aggregator, performance or trace data to a file or locationexternal to memory 122. In various embodiments, the step of storing caninclude detecting, by the aggregator, a change to a data flag set inshared memory allocations 122B-N by the aggregator. If the aggregatordetects a change in a data flag for a particular memory allocation 122C,the aggregator can read data from the shared memory having a changedflag and write the data to the aggregator's buffer 122A. If theaggregator does not detect a change in a data flag for a particularmemory allocation 122B, the aggregator can attend to other processingtasks, e.g., detect the status of a data flag for the next shared memoryallocation, and return to check 656A the data flag for the particularmemory allocation 122B at a later time.

The step of storing 664 can comprise writing data from a shared memoryallocation directly to the aggregator's buffer 122A. In someembodiments, the step of storing 664 further comprises processing thedata from the shared memory allocation before writing the processed datato the aggregator's buffer. In some embodiments, the step of storing 664comprises reading data from shared memory allocations 122B-N, processingthe data, and exporting results from the processed data directly to anagent without storing the data in the aggregator's buffer 122A. In someembodiments, the processing of data comprises consolidating the dataobtained from the plurality of packet engines.

In some embodiments, the step of storing 664 further comprisesmaintaining data structures representative of per core statistics anddata structures representative of global statistics. For example, theaggregator 610 can maintain a per core data structure which identifiesindividual services currently managed by each core. The aggregator 610can further maintain a global data structure which identifies on howmany cores a particular service is handled. In certain embodiments, whena new service is added on any packet engine, the packet engine dumps itsperformance data to its shared memory allocation. The aggregator 610 canthen detect the addition of a service and update its per core and globaldata structures. In some embodiments, the addition of a new service isdetected when each packet engine writes its performance or trace data toshared memory in response to a request for performance or trace data. Insome implementations, when a service is deleted from any packet engine,the packet engine dumps its performance data to its shared memoryallocation. The aggregator 610 can then detect the deletion of a serviceand update its per core and global data structures. In some embodiments,the aggregator 610 removes the service from all per core data structuresand the global structure. In some embodiments, the aggregator 610 onlyremoves the service from the global data structure when all packetengines indicate that they no longer manage the service.

In various embodiments, methods 650 for aggregating performance or tracedata comprise consolidating 666, by the aggregator, the performance ortrace data to provide unified performance data 606A or unified tracedata 606B of the multi-core, multi-packet-engine appliance 200. Theunified data can be representative of the appliance as though theappliance comprised a single core. As an example of consolidation, acase where two packet engines 548A, 548B provide service to a pluralityof clients 102A-N from the same server 106A is considered. A firstpacket engine 548B may record in shared memory 122C that it has 3 activeconnections with server 106A for the service and that its traffic volumeto the service is 85 packets per second. The second packet engine 548Amay record in shared memory 122B that is has 4 active connections withserver 106A for the service and its traffic volume to the service is 37packets per second. For this example, the unified data 606 obtained fromthe step of consolidating 666 would represent the appliance 200 ashaving 7 active connections with server 106A for the service and atraffic volume of 122 packets per second.

In some embodiments, the step of consolidating 666 comprises processingperformance data 605P or trace data 605T obtained from the plurality ofpacket engines 548A-N. The processing can include executing macros,functions, routines, or sets of instructions to compile unifiedperformance statistics 606A or unified trace data 606B representative ofthe appliance 200. As an example, the processing can comprise totaling anumber of connections to distinct servers, totaling traffic volume toeach distinct server, totaling a number of hits on each distinct server,obtaining averages or weighted averages of traffic volume to eachdistinct server, interleaving trace data to provide a unified trace,etc. as described above in reference to unified performance data 606Aand unified trace data 606B. In various embodiments, the aggregator 610consolidates the data from the plurality of packet engines 548A-N afterthe data is written to buffer 122A. The step of consolidating canfurther comprise writing the consolidated data 606 to a separatelocation in memory 122 or to a location reserved in the buffer 122A forconsolidated data. In some embodiments, the aggregator consolidates 666the data from the plurality of packet engines after reading the datafrom shared memory allocations 122B-N, and writes the consolidated data606 to buffer 122A, or exports the unified data 606 directly to an agent620A or to a file external to memory 122. In certain embodiments, thestep of consolidating 666 is repeated periodically, e.g., at timeintervals between about 50 milliseconds (ms) and about 500 ms, betweenabout 500 ms and about 5 seconds, between about 5 seconds and about 60seconds.

When consolidating 666 trace data, the aggregator 610 can furtherrepresent the consolidated data in terms of actual processing time,compressed time, or both. As an example, the processing by themulti-core appliance of a stream of packets from a particular server isconsidered. In various embodiments, the stream of packets flows throughand is processed by the multi-core appliance 200. In some embodiments,the packets are parsed to different packet engines which can processtheir allotted portions of the stream at the same time or differenttimes from the other packet engines. A trace representation of thepacket stream in terms of actual processing time would compriseconsolidating the trace data to reflect the total amount of processingtime of each core used in processing the stream of packets, e.g.,concatenating each core's processing segment. A trace representation ofthe packet stream in terms of compressed time would compriseconsolidating the trace data to reflect the time at which each portionof the stream was processed by the appliance. Compressed time couldprovide an indication of multi-packet-engine processing, e.g., a highrate of content handling for a particular time interval(multi-processing) and a low rate of content handling at another timeinterval (single-core-processing) for a stream of packets.

In some embodiments, the step of consolidating 666 further comprisesconsolidating the number of connections to a service from the pluralityof packet engines 548A-N and providing a total number of connections tothe service from the appliance 200. The service can be provided by oneor more servers 102 over the network 104. The total number ofconnections can be a raw total or represent a number of connections fromdistinct clients. (Some clients may have more than one connection to aservice.) In some embodiments, the consolidating 666 further comprisesconsolidating the average response to a service from the plurality ofpacket engines 548A-N, and providing a unified average response time tothe service from the appliance 200. The unified average response timecan be calculated in any one of several ways, e.g., averaging averageresponse times obtained from each packet engine, calculating a weightedaverage such as weighting the average response obtained from each packetengine by the number of connections made to the service by the packetengine.

In some embodiments, the step of consolidating 666 further comprisesconsolidating the number of bytes passed for a service from theplurality of packet engines 548A-N, and providing a total number ofbytes passed for the service by the appliance 200. In someimplementations, the step of consolidating 666 further comprisesconsolidating the number of different servers obtained from theplurality of packet engines 548A-N, and providing as a portion ofunified data a number of distinct servers providing network service viathe appliance 200. The number of different servers may include allactive servers on each packet engine, all recently active servers,servers in a reserve or reuse pool, all past servers, or any combinationthereof. The number of distinct servers can comprise a subset of thedifferent servers having distinct IP addresses.

The step of receiving a request 668 can comprise receiving, by theaggregator, a request for performance data or trace data of theappliance. The request can be received from one or more agents 620. Therequest can be received by the aggregator through an IP port, e.g., viaan established socket connection managed by the agent interface 615. Incertain embodiments, the step of receiving a request 668 compriseslistening 653 on one or more IP ports for a socket connection andreceiving data representative of a request through an IP port. The stepof receiving 668 can further comprise monitoring activities on IP portsmanaged by the agent interface 615. In certain embodiments, the step ofreceiving a request 668 comprises monitoring a data file or location inmemory for a newly entered request and reading the request from the fileor location in memory. In various embodiments, the request comprisesdata identifying elements of performance statistics or trace datadesired by the entity issuing the request, and identifies a destinationfor transmitting a response to the request. In some implementations, arequest comprises command line code, IOCTL's, objects, function calls,or any type and form of executable instructions. The step of receiving668 a request can comprise executing, by the aggregator, the receivedinstructions, or providing the received instructions, or a portionthereof, to each packet processing engine 548A-N.

In various embodiments, the aggregator 610 is adapted to transmit 670consolidated or unified data 606 in response to a received request forthe data. The unified data 606 can be transmitted in any format. Inparticular embodiments, the step of transmitting 670 further comprisesconverting the unified data 606 to a format specified by the agent 620issuing the request. In certain embodiments, the step of transmitting670 comprises exporting the unified data 606 from buffer 120A to agentinterface 615, which in turn can forward the unified data to the agent620 requesting the data. In some embodiments, the step of transmittingcomprises identifying, by the aggregator, a memory location holding theunified data 606. The memory location can be identified to the agentinterface and/or the agent requesting the data whereupon either theagent interface or agent requesting the data can read the unified data606 from the identified memory location.

G. Systems and Methods For Scalable N-Core Stats Aggregation

Referring now to FIG. 6D, one embodiment of a system for aggregatingdata or statistics from cores of a multi-core appliance is depicted. Inbrief overview, the system includes a plurality of cores 548A-N, sharedmemory 112, and an aggregator 610. In various embodiments, one or moreclients may make a request to the aggregator for data or statistics(e.g., performance statistics and trace data) associated with one ormore cores of the multi-core system. The depicted system may beimplemented as a variation, combination, reconfiguration and/orimprovement over any of the embodiments of features described above inconnection with FIG. 6A.

In certain embodiments, the agent interface and/or agent allows a clientto access data or statistics (hereafter sometimes generally referred toas “data” or “statistics”) collected by the aggregator 610. A client maybe any network device (e.g., client 102, server 106, appliance 200,etc), service, virtual machine, virtual service or program that uses thestatistics or provides the statistics to another entity either processedor unprocessed. In certain embodiments, a client may be a devicetransmitting and/or receiving traffic via one or more cores or packetengines of the appliance. In some embodiments, a client may be anadministrative service, monitoring service or other type of service,e.g., an nsnetsvc associated with CITRIX NETSCALER. In otherembodiments, nsnetsvc may be an agent interface for the aggregator andan agent of a client. In still another embodiments, nsnetsvc may be anagent of a client. A nsnetsvc, as a client and/or client agent, maygenerate and/or deliver commands for requesting statistics from theaggregator. A nsnetsvc, as an agent, may deliver or convey clientcommands for requesting statistics from the aggregator.

In some embodiments, a client may request certain events to be reportedin real-time or substantially in real-time. These events may berepresented by statistics of packet processing engines, virtual serversand/or associated member services processed and/or tracked by one ormore cores of the multi-core system. A client may also request forstatistics from performance records, e.g., using a stat command. Aclient may include or provide a dashboard or other interface fororganizing, summarizing and/or presenting statistics to a user orprogram. In some embodiments, a dashboard may process and/or providedata in real-time or substantially in real-time. A client request maycomprise a request for statistics associated with two or more cores of amulti-core system, or statistics for the multi-core system as a singleunit. In one embodiment, for example in the NETSCALER context, a clientmay use a nsconmsg and/or nscollect command in a request. Another clientrequest may comprise a request for statistics associated with aparticular core of a multi-core system.

The system may support and interface with any number of different typesof clients. In some embodiments, and by way of illustration, thedifferent types of clients may be categorized into at least (1)streaming or non-filtered clients, and (2) filtered request-responseclients. Streaming or non-filtered clients may transmit requests thatare sometimes referred to as kernel mode packet engine (KMPE) typerequests. Such requests may include commands such as nsconmsg. Theserequests may communicate with an aggregator on a particular port (suchas 3333), instead of sending IOCTL calls to the kernel of the appliance.The aggregator may be assigned to and/or listening on the particularport. In some embodiments, streaming clients may parse raw and/or fullperformance data streams (sometimes generally referred to as“perf-streams” or “data streams”) into statistics and/or records.Streaming clients may create and/or maintain the data structures for thestatistics and/or records. Thus, streaming clients may have the same orsubstantially the same access to statistics and information that anaggregator or a packet engine may have. By way of illustration, requestsfrom streaming clients can include nsconmsg, dashboard and nscollectrequests.

The aggregator may support one or more filtered request-responseclients. Request-response clients may send a request for statistics forone or more particular devices (i.e., vservers, packet engines and/orcores). These devices may already be known or identified by the client.The client may already be in communication with these devices. Forexample, the multi-core system may have assigned a particular core toprocess network traffic associated with the client, or the client mayhave previously communicated a packet via a specific packet engine orcore. Responsive to such a request, the aggregator may filter and/orprocess the statistics gathered at the aggregator, generate a responseand/or send the response responsive to a client request. In someembodiments, however, per-entity, e.g., per-core or per-packet-enginestatistics may not be available. For example, per-core statistics maynot be available because statistics for two or more cores or packetengines may have already been merged together. By way of illustration,and not intended to be limiting in any way, requests fromrequest-response clients may include stat, snmpd, nslcd and showcommands or requests.

As discussed above, the aggregator may collect statistics from entitiessuch as packet engines and consolidate the statistics, for example,based on counter definitions. The counter definitions may specify aninterval, schedule and/or sequence for collecting statistics from eachpacket engine. The statistics may be of any type or form, such assummation, average, minimum and maximum per-packet-engine (sometimesreferred to generally as “per-PE”) values. The aggregator may createper-PE records based on the collected statistics and may consolidatethese records to an internal buffer of the aggregator. The aggregatormay parse statistics from each of the packet engines. The aggregator maystore or maintain the per-PE statistics prior to consolidation. Incertain embodiments, the aggregator consolidates and stores the packetengine statistics into the internal buffer. In some embodiments, one ormore clients may access information from the internal buffer. In otherembodiments, the aggregator generates a response to a client requestusing information from the internal buffer. The internal buffer may beor incorporate any type or form of memory device such as cache 140,storage 128, memory 122, 264, buffer 243 and disks 428 described abovein connection with FIGS. 1E-F, 2A and 4A. The aggregator may alsoperform multi-tasking or interleaving between any of the above tasks tocheck for client requests and/or respond to client requests.

In some embodiments, the aggregator may allocate memory and/or datastructures to maintain or manage mappings between local deviceidentifiers and global device identifiers. Local device identifiers maybe assigned on a per-PE or per core basis. In certain embodiments, theaggregator may assign a local device identifier to a entity such as apacket engine, virtual service, virtual machine, service, application orsome other packet processing module in a core. In some embodiments, eachentity may be assigned one or more device identifiers. For example, eachpacket engine or core may execute, provide or be associated with one ormore devices (e.g., virtual servers executing in the core). For example,a vserver v1 executing in connection with PE-0 may have a local devicenumber 100, while a similar vserver executing in connection with PE-1may have local device number that is the same (e.g., 100) or different(e.g., 200) from the vserver v1. Thus, across a plurality of cores,local device numbers of such entities may not be unique. In some ofthese embodiments, the aggregator translates per-PE or local deviceidentifiers to a global device identifier when consolidating statisticsfrom each packet engine. A global device identifier may uniquelyidentify an entity across a plurality of cores.

In some embodiments, each core may operate with the aggregator viashared memory 112. For example, the aggregator may request pages orinformation from a core by writing the request into the shared memory.The core may receive the request by accessing the shared memory 112. Theaggregator 610 may read the requested pages or information from theshared memory. The aggregator may process the requested pages orinformation and store them in an internal buffer of the aggregator,which may be local memory (e.g., of the aggregator, not shared memory).In response to a client request, the aggregator may establish a socketconnection with the corresponding client or client agent. The socketconnection may be used to read and/or write IOCTL messages, e.g., fromthe client to a nsnetsvc, and from the nsnetsvc to the aggregator.

One core may provide data to the aggregator using one or more dedicatedmemory locations. In certain embodiments, an aggregator may share orreuse one or more memory locations between different cores, e.g., atdifferent times.

The aggregator, in processing the statistics, may have certain memoryrequirements. For example and in some embodiments, processing absoluterecords from a packet engine may involve the following:

Collecting stats=100 ms.

Parse the stats=1200 ms.

Dump the stats into client buffer=400 ms.

Processing absolute statistics, which may exclude some records such asdevicename, devlink, codeinfo records, may involve the following:

Collecting stats=100 ms.

Parse the stats=1045 ms.

Dump the stats into client buffer=400 ms.

Processing differential statistics (e.g., incremental changes or updatesto the statistics) may involve the following:

Collecting stats=10 ms.

Parse the stats=200 ms.

Dump the stats into client buffer=400 ms.

The total number of devices established, created, deployed and/ormonitored in a configuration may be 200K=2*10⁵. The total number ofdevice statistics records maintained in the aggregator may be 2M=2*10⁶.The per device counter may be set to 10. Each batch of device statisticsmay take up at least 24 bytes (current, previous and earlier batches)for example. Earlier batches of data may be used for maintaining ratecalculations. The total per-PE statistics space requirement in theaggregator may be 24*2*10⁶ bytes=48 MB. In some embodiments, undernormal traffic patterns, per device counters may be assumed to beapproximately 20-30 (e.g., instead of 10). According to this scenario,the per-PE statistics memory requirement may be around 100-150 MB ormore. In some embodiments, memory requirements may increase, forexample, when features such as configuration scaling, core scaling andcounter scaling, are added.

In some embodiments, the aggregator may be configured to aggregatestatistics without allocating memory for maintaining per-PE statistics.Each packet engine or packet processing entity may be assigned at leastone global device identifier, e.g., by the appliance or a server, fortransferring or dumping per-PE statistics. The aggregator may store datastructures that map local device identifiers to global deviceidentifiers in shared memory with each core. In certain embodiments, theaggregator may use a single block of shared memory shared across aplurality of cores. In some embodiments, the aggregator may allocate orassign specific memory locations or segments for shared access with aparticular core. By way of illustration and not intended to be limitingin any way, an embodiment of data structures maintained in shared memoryfor managing device identifiers is as follows:

u32bits nspm_cur_global_devno ; /* global devnumber for incrementing *//* structure for handling the device name <-> devnumber mapping*/typedef struct nspm_devnamerec { NS_LIST_ENTRY(nspm_devnamerec) dn_list;/* next in chain */ struct nspm_devnamerec *dn_next_free; /* to maintainthe number of devices in the free list*/ u32bits dn_devno; /* globaldevice number */ u08bits dn_devname_len; /* length of this device name*/ u08bits reserved_1[3]; u08bits *dn_devname; /*Max 192 characters, forexample*/ } nspm_devnamerec_t; typedef struct { struct type *lh_first;/* first element */ u32bits devname_slck; /*lock for this bucket */ }nspm_devnamehead_t; nspm_devnamehead_tnspm_devnamehashheads[NSPM_DEVNAMEHASHSIZE]; u32bitsnspm_getdevnamedevno(u08bits *name);

These structures or application processing interfaces (APIs) may be usedby a packet engine to obtain a unique mapping between a device (e.g.,device name or local device identifier) and a global device identifier.In some embodiments, by using global device identifiers, the aggregatormay directly add per-PE differential statistics and/or assign absolutestatistics to aggregated values. This may enable the aggregator tobypass certain steps, such as the steps of updating per-PE datastructures before updating aggregated values. In certain embodiments,the aggregator does not maintain per-PE statistics. The aggregatorinstead dumps the per-PE data streams unchanged to a log file or memory(e.g., newnslog or buffer) using the global device identifiers numbersor associated markers to distinguish the data streams, PEs or cores.

In certain embodiments, the aggregator may provide a computing orprocess thread (hereafter sometimes generally referred to as “thread”)to a packet engine, e.g., for collecting and updating per-PE statistics.A thread may be any type or form of processing unit, task, code,application, agent, module or computing step(s). A thread may executeindependently of another thread, or may communicate or interoperate withanother thread. A given thread may collect a data or statistics streamfrom a respective packet engine, e.g., directly or via shared memory.The thread may parse, analyze or process the data stream and may updatesome portion of aggregated statistics (e.g., of a given device, packetengine or core). The thread may process or track a respective datastream according to a global device identifier. The thread may write thedata stream or statistics into a logfile or memory unchanged (e.g., asgenerated or recorded by a packet processing engine or a monitorexecuting on a corresponding core) or substantially unchanged. Thethread may write the data stream to a logfile or memory withoutconsolidating data from one or more other entities, devices, packetengines or cores. This multi-threading process, supporting multipleentities across one or more cores, may improve overall processing time.For example, processing time may be reduced because the aggregatorwrites data streams directly into a logfile instead of to an internalbuffer requiring proper formats. Concurrent or parallel processing viamulti-threading may also reduce processing time.

In some embodiments, the aggregator may receive a request from a client.The aggregator may identify the request as a dashboard request for anaggregated data stream. The aggregator may be built, designed and/orconfigured to parse, collect and/or consolidate a plurality of datastreams. The aggregator may generate an aggregated data stream from oneor more data streams or cores. The aggregator may, for example, generatean aggregated data stream in real time, or in response to receiving arequest. Responsive to the request, the aggregator may read or accessone or more data streams and/or modify processing on an aggregated datastream.

The aggregator may create and assign a thread to generate, update,handle or process this aggregated data stream. The aggregator mayprocess and/or write at least a portion of the aggregated data stream tothe internal buffer. The aggregator, client and/or client agent mayestablish a dashboard connection to the internal buffer to access thestored data. In some embodiments, the client or client agent may send amessage to the aggregator when the dashboard connection is closed or nolonger required. Responsive to this message, the aggregator may stopwriting or generating the data stream to the internal buffer.Independent of and/or concurrent with this thread, another aggregatorthread (e.g., a main aggregator thread) may serve one or more clientrequests of the same or a different type (e.g., stat, snmpd, nslcd, showrequests).

In some embodiments, a client may seek access to a data stream handledby the aggregator. The client may initiate the request via a nsconsmg ornscollect request. The corresponding client or agent may access the datastream by connecting to a port of the aggregator (e.g.,NSAGG_LISTEN_PORT). The client or agent may issue IOCTL calls via theport (e.g., NSAPI_ADD_RET_PERFDATAHEADER, NSAPI_ADDPERFDATAHEADER,NSAPI_WAITRACEDATA, NSAPI_GETRACEDATA and NSAPI_GETFIRSTRACEDATA) toaccess the internal buffers of the aggregator.

In other embodiments, a client or client agent may access a performancestream from a logfile (e.g., a newnslog file) or a storage device thatreceives or buffers the data stream. The logfile or storage device mayreside anywhere on the network, such as on the aggregator or incommunication with the aggregator. The data streams or statistics may beretrieved from the logfile or storage device instead of from theaggregator (e.g., from local buffers of the aggregator). The aggregatormay directly write at least a portion of the data stream into thelogfile or storage device. A network service or agent, for exampleoperating on behalf of the client, may access the data stream from thelogfile or storage device.

In some embodiments, a client request may initiate or execute a programor instructions to collect information from one or more data streams.For example, a nsconmsg request may be associated with a set ofinstructions. These instructions may be compiled into a binary file,executable and/or program file. The compiled instructions may beincorporated or added to a library (e.g., libnsapps). The compiledinstructions may reside or be installed in the aggregator, or accessibleby the aggregator. Instructions associated with various types of clientrequests may be used for debugging purposes, for collecting data streamsfrom the aggregator, and for writing a data stream to a logfile, forexample.

In certain embodiments, the instructions may be executed as a process. Aprocess, such as one associated with the nsconmsg instructions, may bemade event-aware. Such a process may receive a notification when thelogfile or storage device is updated with newer data. The process mayparse or access the newer data responsive to the notification. In someembodiments, and by way of illustration, a disk access may occur every 7seconds for a process to parse new pages added to the logfile or storagedevice. A large configuration may involve disk accesses of 300 pages perpacket engine, for example. On a 7-packet-engine system, for example,8*300 pages may be accessed, which may translate to about 19 MB per 7seconds, or about 2.5 MB per second. These are page reads, which may bepreferred over socket reads. In certain embodiments, a system having atypical configuration may handle about 1-20 pages per 7 seconds.

Storage requirements may be reduced by not having the logfile or storagedevice contain an aggregated data stream. In some embodiments, storagespace levels or savings of 1/(num of PE+1) with respect to thealternative may be achieved. An aggregated data stream may include datacollected in real time and/or from all or some cores and their entities.In some embodiments, portions of data streams (e.g., representative,estimated or sample statistics) are collected from each PE for storagein the logfile or storage device. If aggregated statistics are needed orpreferred, the requesting client may obtain the different data streamsand perform the aggregation (e.g., at the client or by the clientagent). In some embodiments, counter information for doing so caninclude different types of counters (e.g., _TNC/_TNAVG/_TNMAX/_TNMIN,etc.). Each counter may add or provide a data construct, format and/orlocation (e.g., codevalformat) for holding or tracking this information.These counters may be implemented in or by the aggregator.

In some embodiments, a counter may be used to partition and/or identifya data stream from one or more PEs. Data streams from each PE may beinterleaved using the counter, e.g., according to a predeterminedsequence and/or time period for data collection/logging. In certainembodiments, a counter may generate a marker (e.g., a count oridentifier) for insertion with a particular data stream. The marker maybe used to uniquely identify a data stream from a particular sourceentity (e.g., core, packet engine or virtual server). In someembodiments, a marker is generated based on (e.g., to uniquelycorrespond to) a global device identifier of an entity. A marker may,for example, include a global device identifier, or be uniquely mappedor translated into a global device identifier using a mapping table orother means.

In some other embodiments, an aggregated stream may be stored ormaintained in the logfile or storage device. This may reduce the amountof time for a client to obtain consolidated values. Moreover, in certainembodiments that store or maintain an interleaved or aggregated streamin the logfile or storage device, markers for the respective aggregatedstreams may be used for jumping or identifying between data of differentstreams, such that parsing time within the logfile or storage device canbe saved.

In some embodiments, the aggregator may adaptively inform or communicatewith a packet engine to adjust the data stream transfer, dumpinginterval or schedule. For example, there may be situations in which someaggregator threads are operating slower than the data stream dumpinginterval in the packet engine, such as when the processor handling themulti-threads have higher loads or is handling more threads than usual.The dumping interval may be decreased or increased to synchronize thepacket engine data transfer with the aggregator threads. In someembodiments, the aggregator may use flags or other monitoring means totrack operating speed and/or transfer readiness, for example, using theflags described above in connection with FIGS. 6A-C.

The aggregator may adaptively adjust the transfer interval based on thelogfile generation rate. In some embodiments, a packet engine may dump300 pages every 7 seconds. Based on an eleven-PE, for example, logfilegeneration may involve the following: Absolute records withoutstatistics (X) may cover about 1800 pages, which translates to about1800*8*1024 byte or 14 MB of memory. Absolute stats from one PE (Y) maycover about 1200 pages, which translates to about 9.37 MB. Differentialstats from one PE (Z) may cover about 300 pages, which translates toabout 2.34 MB. Based on the above, one set of absolute record forclients on an 11-PE system may translate to about X+(11+1)Y or 126.44MB. An extra unit of memory (Y), as indicated, may be allocated toaccount for the aggregator. In some embodiments, absolute statistics(e.g., dumped when a configuration change happens) may translate toabout (11+1)Y or 112.44 MB. Differential statistics (e.g., at every 7seconds) may translate to about (11+1)Z or 28 MB. In this case, adifferential record may consume about 4 MB per second. If, the logfileis compressed (gzipped) when it reaches a threshold, e.g., 40 MB,compression may be triggered every 70 seconds. Thus, the aggregator mayadaptively or accordingly adjust the rate of transfer or data streamdump between the packet engines, threads and/or the logfile. Forexample, if the aggregator determines that the logfile size isincrementing too fast (e.g., beyond a threshold rate), the aggregatormay lengthen the interval between transfers/dumps.

Referring now to FIG. 6E, an embodiment of steps of a method 680 foraggregating performance statistics from cores of a multi-core system isdepicted. In brief overview, a multi-core system intermediary betweenone or more clients and servers maintains in shared memory of themulti-core system a global device number for each core of the multi-coresystem (681). Each core may include one or more packet enginesprocessing network traffic between the one or more clients and servers.The multi-core system may provide, via an aggregator, a computing threadfor each core of the multi-core system to gather data from thecorresponding core (683). A first computing thread of the aggregator maycollect statistics of network traffic processed by one or more packetengines on a first core (685). The first computing thread may transferthe statistics with a marker to a statistics log of the multi-coresystem (687). The marker may correspond to a global device number of thefirst core. The multi-core system may adaptively reschedule the transferby monitoring the operation of each computing thread (689). In furtherdetails of step 681, a multi-core system intermediary between one ormore clients and servers maintains in shared memory a global deviceidentifier (or number) for each core of the multi-core system. Each coremay include one or more packet engines processing network trafficbetween the one or more clients and servers. An aggregator of the systemmay provide and/or maintain the shared memory. The aggregator mayprovide and/or maintain a block of shared memory for each core, or for aplurality of cores. The aggregator may provide and/or maintain a blockof shared memory for use with one or more packet engines, virtualmachines, applications, services and/or other entities of each core. Forexample, the aggregator may provide and/or maintain a respective portionof the shared memory for use with each packet engine or other entity ofa core.

The aggregator may generate, provide and/or assign one or more globaldevice identifiers to each core or packet engine. The aggregator maygenerate, provide and/or assign one or more global device identifiers toeach entity or device (e.g., packet engines, virtual machines,applications, services and/or other entities of each core). Theaggregator may generate, provide and/or assign a unique global deviceidentifier to each packet engine, virtual machine, application, serviceand/or other entity of a core. For example, the aggregator may assign,for each core of the multi-core system, a global device number to avirtual machine executing on the core. The aggregator may assign, foreach core of the multi-core system, a global device number to eachvirtual machine of the core. Each virtual machine may include one ormore packet engines processing network traffic between the one or moreclients and servers. The aggregator may generate, provide and/or assigna global device identifier that is unique within and/or between cores ofthe multi-core system. The aggregator may generate, provide and/orassign a global device identifier that uniquely identifies an entity ordevice from others within a core and/or between cores of the multi-coresystem.

The aggregator and/or each packet engine may create, maintain and/ormanage a mapping of device names (e.g., local device names) oridentifiers to global device identifiers in the shared memory. Each coreor packet engine may assign a local device name or identifier to eachdevice associated with the core or packet engine, for example, virtualservers executing on the core. The local device name of an entity ordevice may be unique within a core. The local device name may not beunique between cores. The aggregator may use the mapping to determine aglobal device identifier corresponding to a local device name referencedin or identified with a data stream received from a packet engine. Theaggregator may, for example, parse or extract such a local device namefrom the data stream.

In some embodiments, a packet engine or other device writes or transfersa data or performance stream into the shared memory. The aggregator, viaan assigned thread or otherwise, may receive, poll or transfer a datastream from the shared memory, according to a schedule or predeterminedinterval for example. The packet engine may write a data stream from oneor more devices associated with a packet engine or core. The core orpacket engine may provide, assign or reference a device name (e.g.,local device identifier) associated with each data stream. The core orpacket engine may dump or transfer a data stream, or part thereof, tothe shared memory according to a schedule or predetermined interval. Incertain embodiments, the core or packet engine may provide a globaldevice identifier associated with a data stream to the aggregator byusing the device-name to global-device-identifier mapping.

In some embodiments, the aggregator determines or identifies a globaldevice identifier for the device or entity generating the data stream.The aggregator may determine a global device identifier based on a localdevice identifier referenced in the data stream and/or the identity ofthe device or entity generating the data stream. The aggregator mayassociate the global device identifier with the data stream. In someembodiments, the aggregator stores the mapping and/or global deviceidentifiers in the shared memory. The mapping may comprise any type orform of table, database or data structure for storing and/or organizingthe global device identifiers. In further details of step 683, anaggregator of the multi-core system may execute a computing thread foreach core of the multi-core system. An aggregator of the multi-coresystem may execute a computing thread on a processor or processingresource of the aggregator. In some embodiments, the aggregator executesa computing thread on a processor or processing resource assigned to theaggregator. In certain embodiments, the aggregator executes acorresponding thread in memory shared or associated with a core. Theaggregator or multi-core system may provide a computing thread for eachcore of the multi-core system to gather data from the correspondingcore. The computing thread may access shared memory to gather data orsome portion of a data stream provided from a core.

The aggregator may provide a thread to operate with each active core orpacket engine. The aggregator may create or execute a thread to operatewith a core responsive to the core powering up, entering an active mode,or processing one or more packets. In some embodiments, the aggregatormay provide a thread to operate with each entity or device of a core. Aprocessor of the aggregator, or a processing resource assigned to theaggregator, may provide multi-threading support to handle a plurality ofcores of the system. The aggregator may maintain one or more threads tohandle data generated by one or more cores and/or client requests (e.g.,for performance statistics or trace data).

In certain embodiments, a block of shared memory is assigned to acorresponding thread and a packet engine or core. The aggregator mayallocate or assign memory to a core that is accessible by both the coreand a corresponding thread. A thread may perform polling on the sharedmemory to detect and receive data streams (e.g., statistics of networktraffic) dumped by a respective packet engine, entity or device. In someembodiments, a packet engine, entity or device informs a respectivethread that a data stream is available. The thread may identify a globaldevice identifier for a data stream, either determined by a respectivepacket engine, or by translating a device number associated with thepacket engine or data stream using the mapping information. In furtherdetails of step 685, a first computing thread of the aggregator maycollect statistics of network traffic processed by one or more packetengines on a first core. A first computing thread may generateaggregated statistics from a corresponding core by parsing the gathereddata from the corresponding core. The thread may parse one or more datastreams from a core or packet engine for consolidation into aggregatedstatistics. In some embodiments, the first computing thread may buffer,interleave and/or consolidate data streams or statistics from two ormore packet engines or entities of a core. A thread may access one ormore data stream dumps from the shared memory. The thread may access oneor more data streams according to a schedule or predetermined interval.The thread may parse a data stream to identify one or more pieces ofinformation. The thread may parse, sample or filter the data stream intoa processed stream. The thread may extract information from a datastream to compute or determine statistics (e.g., performance and/ortrace statistics) for a device of the core. In some embodiments, athread may be assigned to handle client requests, such as a request(e.g., stat, snmpd, show, nslcd) from a filtered request-responseclient. This thread may operate independently of any core or packetengine of the multi-core system. The thread may communicate with aclient or agent, for example via an agent interface 615. In someembodiments, the thread communicates with a client or agent via a port(e.g., port 5555). The thread may access one or more data streamsresponsive to a client request. For example and in some embodiments, thethread may access a data stream (e.g., via shared memory) based on aglobal device number identified by a client or agent. The thread mayparse, filter, extract or otherwise process a data stream to generatestatistics responsive to the client request. This thread may execute andoperate independent of other aggregator threads and/or packet engines.In some embodiments, the thread may process data streams according to anadaptively-generated or adjusted schedule, which may depend on theprocessing speed of the thread and/or the transfer rate of a packetengine.

In some embodiments, a thread may be assigned to handle client requests,such as a request (e.g., dashboard request) from a streaming client. Thethread and/or the aggregator may write at least a portion of a datastream into an internal buffer of the aggregator based on or responsiveto the request. In some embodiments, the aggregator may generateaggregated statistics for one or more cores responsive to receiving aclient request, e.g., identifying the one or more cores. For example,the aggregator may consolidate at least a portion of the statisticscollected from two or more cores of the multi-core system into a buffer.In some embodiments, a data stream may be identified by a global deviceidentifier in a client request. In certain embodiments, the threadand/or the aggregator may parse, filter, extract and/or process one ormore identified data streams to generate statistics, e.g, aggregatedstatistics, for storing into the internal buffer.

A client or agent of the client may access the internal buffer for therequested information. In some embodiments, the thread buffers therequested information in the internal buffer for transmission (e.g., viaa dashboard connection) to a dashboard, agent or client. In someembodiments, a client or agent may communicate to the thread thatfurther information is no longer required or requested, or that thedashboard connection is closed. Responsive to this communication, thethread may halt aggregation and/or writing of data into the internalbuffer.

In further details of step 687, the first computing thread may transferthe statistics with a marker to a statistics log of the multi-coresystem. The marker may correspond to a global device number of the firstcore. The first computing thread may transfer the generated statisticsto a statistics log according to a schedule. The first computing threadmay write collected statistics to the statistics log according to aschedule generated and/or maintained by the aggregator. The threadassigned to a core or packet engine may parse and/or process one or moredata streams from the core or packet engine into aggregated statisticsor aggregated data streams. In some embodiments, the thread writes orstores the processed data into a logfile or storage device (e.g.,residing on the appliance or another device). The thread may, in someembodiments, write or store the processed data in an internal or localbuffer of the aggregator.

In certain embodiments, the thread writes or stores each data streamunchanged or substantially unchanged into the logfile or storage device.For example, the first computing thread may transfer the collectedstatistics unchanged to the statistics log. The thread may transfer adata stream directly from shared memory to the logfile or storagedevice. Each thread may store or interleave a respective data streaminto the logfile or storage device accordingly to a schedule orpredetermined interval. In certain embodiments, the aggregator maycreate an aggregated data stream from one or more data streams, forstoring into the logfile or storage device.

The multi-core system may, for example via the aggregator, maintain thestatistics log for two or more cores of the multi-core system. Themulti-core system may separate, partition, segment the statistics logusing the markers and/or global device identifiers. The multi-coresystem may interleave, identify and/or mark portions of the statisticslog to record or store data from different cores or devices of themulti-core system. In some embodiments, a marker or global deviceidentifier may mark the start of data specific to a corresponding coreor device in the statistics log. In certain embodiments, a marker orglobal device identifier may mark the end of data specific to acorresponding core or device in the statistics log.

In some embodiments, the multi-core system provides one or more clientsor their agents with access to the statistics log. The multi-core systemmay provide an interface, such as an applications processing interface,through which a client or agent can read or access the statistics log.In certain embodiments, the multi-core system provides the statisticslog in text form. The multi-core system may provide the statistics login any standardized format that a client can read, interpret and/orprocess. The aggregator may, in some embodiments, generate and/or send anotification to a first client of the one or more clients responsive toa transfer to the statistic log.

In further details of step 689, the multi-core system adaptivelyreschedules the transfer by monitoring the operation of each computingthread. The multi-core system may adaptively reschedule the transfer bymonitoring the operation of each computing thread, core, packet engineand/or other entity of a core. For example, the aggregator mayadaptively reschedule the transfer by monitoring the operation of thefirst core. The aggregator or the system may adaptively modify or adjusta schedule or interval for transferring data by one or more packetengines and threads. The aggregator may determine that one or morethreads are operating slower than the respective packet engines.

The aggregator may determine that the dumping schedule or intervalshould be adjusted to synchronize operation between one or more packetengines and threads. The aggregator may determine that the logfile sizeis increasing at a rate beyond a predetermined threshold. The aggregatormay determine or detect a change in the creation rate or transfer rateof one or more data streams. The aggregator may determine a change inthe frequency of client requests. Responsive to the determination, theaggregator may adaptively modify or adjust a schedule or interval fortransferring data between one or more cores, packet engines, sharedmemory, threads, internal buffers and/or logfiles.

A client or client agent may parse or extract particular portions of thestatistics log using the markers or global device identifiers. Forexample, a client agent may extract statistics corresponding to aparticular core or global device identifier for processing. In someembodiments, a client or client agent process the statistics log togenerate aggregated statistics corresponding to one or more cores orglobal device identifiers. In some embodiments, responsive to a requestfrom a client, an agent obtains data stored in the logfile forconsolidation or aggregation at the client. In some embodiments, aclient or agent may prefer or need consolidated or aggregated statisticsfor the multi-core system. The client or agent may access the logfile orstorage device for one or more stored data streams. The client mayprocess the one or more data streams, at the client, into aggregateddata streams and/or statistics. In some embodiments, the client or agentmay access the logfile or storage device for an aggregated data stream.The client may process the aggregated data stream, at the client, intoconsolidated statistics.

In some embodiments, multiple client requests and/or multiple type ofclient requests may occur concurrently or sequentially. A main thread ofthe aggregator for example, may process a request from a filteredrequest-response client, while another client or agent may access thelogfile in connection with a nsconmsg/nscollect request. In certainembodiments, a streaming client request (e.g., dashboard request) may beprocessed by providing the requested data via the internal buffer of theaggregator. The latter may be handled by another thread of theaggregator, in parallel with the other client requests. Various threadsmay operate independently or in a coordinated fashion (e.g., adaptivelycoordinated by the aggregator in sequence).

It should be understood that the systems described above may providemultiple ones of any or each of those components and these componentsmay be provided on either a standalone machine or, in some embodiments,on multiple machines in a distributed system. In addition, the systemsand methods described above may be provided as one or morecomputer-readable programs or executable instructions embodied on or inone or more articles of manufacture. The article of manufacture may be afloppy disk, a hard disk, a CD-ROM, a flash memory card, a PROM, a RAM,a ROM, or a magnetic tape. In general, the computer-readable programsmay be implemented in any programming language, such as LISP, PERL, C,C++, C#, PROLOG, or in any byte code language such as JAVA. The softwareprograms or executable instructions may be stored on or in one or morearticles of manufacture as object code.

While the invention has been particularly shown and described withreference to specific embodiments, it should be understood by thoseskilled in the art that various changes in form and detail may be madetherein without departing from the spirit and scope of the invention asdisclosed herein.

1. A method for aggregating performance statistics from multiple coresof a system intermediary between one or more clients and servers, themultiple cores processing multiple network traffic streams between oneor more clients and servers, the method comprising: (a) maintaining, inshared memory of a multi-core system intermediary between one or moreclients and servers, a global device number for each core of themulti-core system, each core comprising one or more packet enginesprocessing network traffic between the one or more clients and servers;(b) executing, by an aggregator of the multi-core system, a computingthread for each core of the multi-core system; (c) collecting, by afirst computing thread of the aggregator, statistics of network trafficprocessed by one or more packet engines on a first core; and (d)transferring, by the first computing thread, the statistics with amarker to a statistics log of the multi-core system, the markercorresponding to a global device number of the first core.
 2. The methodof claim 1, wherein (a) further comprises assigning, for each core ofthe multi-core system, a global device number to a virtual machineexecuting on the core.
 3. The method of claim 1, wherein (a) furthercomprises assigning, for each core of the multi-core system, a globaldevice number to each virtual machine of the core, each virtual machinecomprising one or more packet engines processing network traffic betweenthe one or more clients and servers.
 4. The method of claim 1, wherein(c) further comprises consolidating, by the aggregator, at least aportion of statistics collected from two or more cores of the multi-coresystem into a buffer.
 5. The method of claim 1, wherein (d) furthercomprises writing the collected statistics to the statistics logaccording to a schedule of the aggregator.
 6. The method of claim 5,wherein (d) further comprises adaptively rescheduling, by theaggregator, the transfer by monitoring the operation of the first core.7. The method of claim 1, wherein (d) further comprises transferring thecollected statistics unchanged to the statistics log.
 8. The method ofclaim 1, wherein (d) further comprises maintaining, by the multi-coresystem, the statistics log for two or more cores of the multi-coresystem.
 9. The method of claim 1, further comprising sending, by theaggregator, a notification to a first client of the one or more clientsresponsive to the transfer.
 10. The method of claim 1, furthercomprising providing, by the multi-core system to the one or moreclients, access to the statistics log.
 11. A system for aggregatingperformance statistics from multiple cores of a device intermediarybetween one or more clients and servers, the multiple cores processingmultiple network traffic streams between one or more clients andservers, the system comprising: shared memory between multiple cores ofthe intermediary device, for maintaining a global device number for eachcore of the multi-core system, each core comprising one or more packetengines processing network traffic between the one or more clients andservers; and an aggregator of the intermediary device, executing acomputing thread for each core of the multi-core system, comprising afirst computing thread collecting statistics of network trafficprocessed by one or more packet engines on a first core, andtransferring the statistics with a marker to a statistics log of themulti-core system, the marker corresponding to a global device number ofthe first core.
 12. The system of claim 11, wherein the aggregatorassigns a global device number to a virtual machine executing on eachcore.
 13. The system of claim 11, wherein the aggregator assigns aglobal device number to each virtual machine of each core, each virtualmachine comprising one or more packet engines processing network trafficbetween the one or more clients and servers.
 14. The system of claim 11,wherein the aggregator further consolidates at least a portion ofstatistics collected from two or more cores of the multi-core systeminto a buffer.
 15. The system of claim 11, wherein the first computingthread writes the collected statistics to the statistics log accordingto a schedule of the aggregator.
 16. The system of claim 15, wherein theaggregator adaptively reschedules the transfer by monitoring theoperation of the first core.
 17. The system of claim 11, wherein thefirst computing thread transfers the collected statistics unchanged tothe statistics log.
 18. The system of claim 11, wherein the aggregatormaintains the statistics log for two or more cores of the device. 19.The system of claim 11, wherein the aggregator sends a notification to afirst client of the one or more clients responsive to the transfer. 20.The system of claim 11, wherein the aggregator provides the one or moreclients access to the statistics log.